Are you looking for the Best Book On Reinforcement Learning? If so, you’ve come to the right place.
Choosing the Best Book On Reinforcement Learning can be difficult as there are so many considerations, such as Crayola, Elsevier, Hasbro, LEGO, Nintendo, Penguin Random House, TopQ, Amazon.com. We have done a lot of research to find the Top 20 Best Book On Reinforcement Learning available.
The average cost is $65.82. Sold comparable range in price from a low of $8.88 to a high of $293.93.
Based on the research we did, we think Reinforcement Learning: An Introduction [Book] is the best overall. Read on for the rest of the great options and our buying guide, where you can find all the information you need to know before making an informed purchase.
20 Best Book On Reinforcement Learning (18 Sellers)
Product Image |
Product Name |
Features |
Check Price |
|
|
-
- Binding type: hardback
- Year published: 20181113
- Number of pages: 552
|
|
|
|
-
- Binding type: paperback
- Publisher: springer verlag, singapore
- Year published: 2022-06-12
|
|
|
|
-
- Focus on the foundational theory underpinning reinforcement learning and software design of the corresponding models and algorithms.
- Suitable for a professional audience of quantitative analysts or data scientists.
|
|
|
|
-
- Key features.
- Structuring problems as markov decision processes.
- Popular algorithms such deep q-networks, policy gradient method and evolutionary algorithms and the intuitions that drive them.
|
|
|
|
-
- Binding type: paperback
- Year published: 2020-11-10
- Number of pages: 465
|
|
|
|
-
- Builds a story about the power of teachers, feedback, and a model of learning and understanding.
- This book covers areas such as the influence of the student, home, school, curricula, teacher, and teaching strategies.
- It develops a model of teaching and learning based on the notion of visible teaching and visible learning.
|
|
|
|
-
- Can i set limits and still be a loving person
- What are legitimate boundaries
- How do i effectively manage my digital life so that it doesn't control me
|
|
|
|
-
- Grand central pub
- Brand: grand central publishing
- Easy to understand
|
|
|
|
-
- Learn what rl is and how the algorithms help solve problems
- Become grounded in rl fundamentals including markov decision processes, dynamic programming, and temporal difference learning
- Dive deep into a range of value and policy gradient methods
|
|
|
|
-
- Binding type: paperback
- Year published: 2022-07-26
- Number of pages: 568
|
|
|
|
-
- Why sometimes letting your mind wander is an important part of the learning process.
- How to avoid rut think in order to think outside the box.
- Why having a poor memory can be a good thing.
|
|
|
|
-
- Languages: english
- Product format: hardback
- Publisher: random house usa
|
|
|
|
-
- Library journal (starred review) everyone should read this book.
- Chip heath and dan heath, authors of made to stick one of the most influential books ever about motivation.
- Po bronson, author of nurtureshock if you manage people or are a parent (which is a form of managing people), drop everything and read mindset.
|
|
|
|
-
- The book might be ex-library copy and may have the markings and stickers associated from the library.
- The book may have considerable highlights/notes/underlined pages but the text is legible.
- Safe and secure mailer.
|
|
|
|
-
- Power of habits
- Brand: random house trade
- Can be considered as a gifting option/ perfect for gifting purpose
|
|
|
|
-
- Trial-and-error search and delayed reward.
- Are the most important distinguishing features of reinforcement learning.
|
|
|
|
-
- Trial-and-error search and delayed reward.
- Are the most important distinguishing features of reinforcement learning.
|
|
|
|
-
- Series: foundations and trends in machine learning
- Binding type: paperback
- Publisher: now publishers inc
|
|
|
|
-
- After completing this book, you will understand reinforcement learning with deep q and generative adversarial networks using the tensorflow library.
- What you will learn.
- Understand the fundamentals of reinforcement learning.
|
|
|
|
-
- After completing this book, you will understand reinforcement learning with deep q and generative adversarial networks using the tensorflow library.
- What you will learn.
- Understand the fundamentals of reinforcement learning.
|
|
Features:
- Binding type: hardback
- Year published: 20181113
- Number of pages: 552
Features:
- Binding type: paperback
- Publisher: springer verlag, singapore
- Year published: 2022-06-12
Features:
- Focus on the foundational theory underpinning reinforcement learning and software design of the corresponding models and algorithms.
- Suitable for a professional audience of quantitative analysts or data scientists.
Features:
- Key features.
- Structuring problems as markov decision processes.
- Popular algorithms such deep q-networks, policy gradient method and evolutionary algorithms and the intuitions that drive them.
Features:
- Binding type: paperback
- Year published: 2020-11-10
- Number of pages: 465
Features:
- Builds a story about the power of teachers, feedback, and a model of learning and understanding.
- This book covers areas such as the influence of the student, home, school, curricula, teacher, and teaching strategies.
- It develops a model of teaching and learning based on the notion of visible teaching and visible learning.
Features:
- Can i set limits and still be a loving person
- What are legitimate boundaries
- How do i effectively manage my digital life so that it doesn't control me
Features:
- Grand central pub
- Brand: grand central publishing
- Easy to understand
Features:
- Learn what rl is and how the algorithms help solve problems
- Become grounded in rl fundamentals including markov decision processes, dynamic programming, and temporal difference learning
- Dive deep into a range of value and policy gradient methods
Features:
- Binding type: paperback
- Year published: 2022-07-26
- Number of pages: 568
Features:
- Why sometimes letting your mind wander is an important part of the learning process.
- How to avoid rut think in order to think outside the box.
- Why having a poor memory can be a good thing.
Features:
- Languages: english
- Product format: hardback
- Publisher: random house usa
Features:
- Library journal (starred review) everyone should read this book.
- Chip heath and dan heath, authors of made to stick one of the most influential books ever about motivation.
- Po bronson, author of nurtureshock if you manage people or are a parent (which is a form of managing people), drop everything and read mindset.
Features:
- The book might be ex-library copy and may have the markings and stickers associated from the library.
- The book may have considerable highlights/notes/underlined pages but the text is legible.
- Safe and secure mailer.
Features:
- Power of habits
- Brand: random house trade
- Can be considered as a gifting option/ perfect for gifting purpose
Features:
- Trial-and-error search and delayed reward.
- Are the most important distinguishing features of reinforcement learning.
Features:
- Trial-and-error search and delayed reward.
- Are the most important distinguishing features of reinforcement learning.
Features:
- Series: foundations and trends in machine learning
- Binding type: paperback
- Publisher: now publishers inc
Features:
- After completing this book, you will understand reinforcement learning with deep q and generative adversarial networks using the tensorflow library.
- What you will learn.
- Understand the fundamentals of reinforcement learning.
Features:
- After completing this book, you will understand reinforcement learning with deep q and generative adversarial networks using the tensorflow library.
- What you will learn.
- Understand the fundamentals of reinforcement learning.
1. Reinforcement Learning: An Introduction [Book]
Product Details:
The significantly expanded and updated new edition of a widely used text on reinforcement learning, one of the most active research areas in artificial intelligence.reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives while interacting with a complex, uncertain environment. in reinforcement learning, richard sutton and andrew barto provide a clear and simple account of the field's key ideas and algorithms. this second edition has been significantly expanded and updated, presenting new topics and updating coverage of other topics.like the first edition, this second edition focuses on core online learning algorithms, with the more mathematical material set off in shaded boxes. part i covers as much of reinforcement learning as possible without going beyond the tabular case for which exact solutions can be found. many algorithms presented in this part are new to the second edition, including ucb, expected sarsa, and double learning. part ii extends these ideas to function approximation, with new sections on such topics as artificial neural networks and the fourier basis, and offers expanded treatment of off-policy learning and policy-gradient methods. part iii has new chapters on reinforcement learning's relationships to psychology and neuroscience, as well as an updated case-studies chapter including alphago and alphago zero, atari game playing, and ibm watson's wagering strategy. the final chapter discusses the future societal impacts of reinforcement learning.
Reviews:
Nicely packaged and arrived right on time.us_rubay
2. Deep Reinforcement Learning [Book]
Product Details:
Deep reinforcement learning has attracted considerable attention recently. impressive results have been achieved in such diverse fields as autonomous driving, game playing, molecular recombination, and robotics. in all these fields, computer programs have taught themselves to understand problems that were previously considered to be very difficult. in the game of go, the program alphago has even learned to outmatch three of the world’s leading players.deep reinforcement learning takes its inspiration from the fields of biology and psychology. biology has inspired the creation of artificial neural networks and deep learning, while psychology studies how animals and humans learn, and how subjects’ desired behavior can be reinforced with positive and negative stimuli. techniques that are inspired by biology and psychology work amazingly well in computers: animal behavior and the structure of the brain as new blueprints for science and engineering. in fact, computers truly seem to possess aspects of human behavior; as such, this field goes to the heart of the dream of artificial intelligence. these research advances have not gone unnoticed by educators. many universities have begun offering courses on the subject of deep reinforcement learning. the aim of this book is to provide an overview of the field, at the proper level of detail for a graduate course in artificial intelligence. it covers the complete field, from the basic algorithms of deep q-learning, to advanced topics such as multi-agent reinforcement learning and meta learning.
Specifications:
Imprint |
Springer |
Pub date |
01 Jul 2022 |
DEWEY edition |
23 |
Language |
English |
Spine width |
28mm |
3. Foundations Of Reinforcement Learning With Applications In Finance [Book]
Product Details:
Foundations of reinforcement learning with applications in finance aims to demystify reinforcement learning, and to make it a practically useful tool for those studying and working in applied areas — especially finance.reinforcement learning is emerging as a powerful technique for solving a variety of complex problems across industries that involve sequential optimal decisioning under uncertainty. its penetration in high-profile problems like self-driving cars, robotics, and strategy games points to a future where reinforcement learning algorithms will have decisioning abilities far superior to humans. but when it comes getting educated in this area, there seems to be a reluctance to jump right in, because reinforcement learning appears to have acquired a reputation for being mysterious and technically challenging. this book strives to impart a lucid and insightful understanding of the topic by emphasizing the foundational mathematics and implementing models and algorithms in well-designed python code, along with robust coverage of several financial trading problems that can be solved with reinforcement learning. this book has been created after years of iterative experimentation on the pedagogy of these topics while being taught to university students as well as industry practitioners.features focus on the foundational theory underpinning reinforcement learning and software design of the corresponding models and algorithms suitable as a primary text for courses in reinforcement learning, but also as supplementary reading for applied/financial mathematics, programming, and other related courses suitable for a professional audience of quantitative analysts or data scientists blends theory/mathematics, programming/algorithms and real-world financial nuances while always striving to maintain simplicity and to build intuitive understanding.
Specifications:
Language |
English |
Dimensions |
7 x 1.37 x 10 inches |
Print length |
522 pages |
Hardcover |
522 pages |
4. Deep Reinforcement Learning In Action [Book]
Product Details:
This reinforcement process can be applied to computer programs allowing them to solve more complex problems that classical programming cannot. deep reinforcement learning in action teaches you the fundamental concepts and terminology of deep reinforcement learning, along with the practical skills and techniques you’ll need to implement it into your own projects. purchase of the print book includes a free ebook in pdf, kindle, and epub formats from manning publications. about the technology deep reinforcement learning ai systems rapidly adapt to new environments, a vast improvement over standard neural networks. a drl agent learns like people do, taking in raw data such as sensor input and refining its responses and predictions through trial and error. about the book deep reinforcement learning in action teaches you how to program ai agents that adapt and improve based on direct feedback from their environment. in this example-rich tutorial, you’ll master foundational and advanced drl techniques by taking on interesting challenges like navigating a maze and playing video games. along the way, you’ll work with core algorithms, including deep q-networks and policy gradients, along with industry-standard tools like pytorch and openai gym. what's inside building and training drl networks the most popular drl algorithms for learning and problem solving evolutionary algorithms for curiosity and multi-agent learning all examples available as jupyter notebooks about the reader for readers with intermediate skills in python and deep learning. about the author alexander zai is a machine learning engineer at amazon ai. brandon brown is a machine learning and data analysis blogger. table of contents part 1 – foundations 1. what is reinforcement learning? 2. modeling reinforcement learning problems: markov decision processes 3. predicting the best states and actions: deep q-networks 4. learning to pick the best policy: policy gradient methods 5. tackling more complex problems with actor-critic methods part 2 – above and beyond 6. alternative optimization methods: evolutionary algorithms 7. distributional dqn: getting the full story 8. curiosity-driven exploration 9. multi-agent reinforcement learning 10. interpretable reinforcement learning: attention and relational models 11. in conclusion: a review and roadmap
Reviews:
A great introduction to all concepts required to understand a challenging subject like deep reinforcement learning.Using PyTorch, the latest array analysis framework.Ahmed A
I've scored the book after reading only two chapters. Seems valuable.
The book is written for humans and is a great supplement for old reinforcement learning books which focus mainly on mathematics behind (policy gradient theorem, q function approximations etc.) I wouldnt recommend to use this book without mathematically oriented ones, because it misses too many important details. It is definitelly a great book which shows many examples together with explanations which are more practically oriented.Frankie
5. Grokking Deep Reinforcement Learning [Book]
Product Details:
Grokking deep reinforcement learning uses engaging exercises to teach you how to build deep learning systems. this book combines annotated python code with intuitive explanations to explore drl techniques. this common pattern is the foundation of deep reinforcement learning: building machine learning systems that explore and learn based on the responses of the environment. grokking deep reinforcement learning introduces this powerful machine learning approach, using examples, illustrations, exercises, and crystal-clear teaching. you'll love the perfectly paced teaching and the clever, engaging writing style as you dig into this awesome exploration of reinforcement learning fundamentals, effective deep learning techniques, and practical applications in this emerging field. purchase of the print book includes a free ebook in pdf, kindle, and epub formats from manning publications. deep reinforcement learning brings that same natural process to artificial intelligence, analyzing results to uncover the most efficient ways forward. drl agents can improve marketing campaigns, predict stock performance, and beat grand masters in go and chess. about the book grokking deep reinforcement learning uses engaging exercises to teach you how to build deep learning systems. this book combines annotated python code with intuitive explanations to explore drl techniques. you’ll see how algorithms function and learn to develop your own drl agents using evaluative feedback. what's inside an introduction to reinforcement learning drl agents with human-like behaviors applying drl to complex situations about the reader for developers with basic deep learning experience. about the author miguel morales works on reinforcement learning at lockheed martin and is an instructor for the georgia institute of technology’s reinforcement learning and decision making course. table of contents 1 introduction to deep reinforcement learning 2 mathematical foundations of reinforcement learning 3 balancing immediate and long-term goals 4 balancing the gathering and use of information 5 evaluating agents’ behaviors 6 improving agents’ behaviors 7 achieving goals more effectively and efficiently 8 introduction to value-based deep reinforcement learning 9 more stable value-based methods 10 sample-efficient value-based methods 11 policy-gradient and actor-critic methods 12 advanced actor-critic methods 13 toward artificial general intelligence
Reviews:
Excellent content. The content is complemented with code on Github which I can clone and run on my own. This helped me to grasp the material quicker. Thank you!Amit M
The content of this book is comprehensive. But it would be better to use with video tutorials to gain a better comprehension.Jim C
Clear and to the point. Covers most important aspects of the subject in an elegant way. The accompanying code is excellent.
6. Visible Learning: A Synthesis Of Over 800 Meta-Analyses Relating To Achievement [Book]
Product Details:
"visible learning is the definitive book on sorting out the effectiveness of teaching strategies – a must read for those who want to improve teaching and learning." -michael fullan this unique and ground-breaking book is the result of 15 years' research and synthesizes over 800 meta-analyses relating to the influences on achievement in school-aged students. it builds a story about the power of teachers and of feedback, and constructs a model of learning and understanding. visible learning presents research involving many millions of students and represents the largest ever collection of evidence-based research into what actually works in schools to improve learning. areas covered include the influences of the student, home, school, curricula, teacher, and teaching strategies. a model of teaching and learning is developed based on the notion of visible teaching and visible learning. a major message within the book is that what works best for students is similar to what works best for teachers. this includes an attention to setting challenging learning intentions, being clear about what success means, and an attention to learning strategies for developing conceptual understanding about what teachers and students know and understand. although the current evidence-based fad has turned into a debate about test scores, this book is about using evidence to build and defend a model of teaching and learning. a major contribution to the field, it is a fascinating benchmark for comparing many innovations in teaching and schools. john hattie is professor of education and director of the visible learning labs, university of auckland, new zealand.
7. Boundaries Updated And Expanded Edition: When To Say Yes, How To Say No To Take Control Of Your Life [Book]
Product Details:
Join the millions who have learned how to take control of their lives by setting healthy boundaries with their spouses, children, friends, parents, coworkers, and even themselves, in order to live life to the fullest.do you feel like your life has spiraled out of control? have you focused so much on being loving and unselfish that you've forgotten your own limits? do you find yourself taking responsibility for other people's feelings and problems? in boundaries, drs. henry cloud and john townsend teach you the ins and outs of setting the boundaries that will transform your daily life.boundaries, a new york times bestseller, will give you the tools you need to learn to say yes and know how to say no. drs. henry cloud and john townsend are here to share the lessons they've learned in their years of practicing psychology and studying the patterns and practices that support clear biblical boundaries.since it was first published, boundaries has supported millions of people around the world as they discover the importance of understanding their limitations and upholding their boundaries. cloud and townsend answer the most common questions they've received in more than thirty years that they've studied the science behind establishing boundaries: can i set limits and still be a loving person? what are legitimate boundaries? how do i effectively manage my digital life so that it doesn't control me? what if someone is upset or hurt by my boundaries? how do i answer someone who wants my time, love, energy, or money? why do i feel guilty or afraid when i consider setting boundaries? how do boundaries relate to mutual submission within marriage? aren't boundaries selfish? discover the countless ways that boundaries can change your life for the better today!
Reviews:
This was highly recommended to.me but I found the constant bible reference and quotes to be off putting. I can normally filter that stuff out but it is really heavy handed and distracting. not my thing. Mite be good for a bible talk group looking to delve into certain topics. If you're religious in thst way you will love it! Aside from that the topics weren't new ideas so I was glad I found it used and cheap. It's not a book I kept.already gonefireheart1313
One of the best books you'll ever buy. And no, don't think it's not for you and that 'it's only for people who need it'. We ALL have boundary issues, and deal with people who have boundary issues. These issues are the main reason for all those relationship issues we have at home, and in the workplace (eg toxic workplaces anyone?). You'll 100% get something good out of it. There's wisdom in practically every page. For those that are not Christian, it has Bible verses (as wisdom references), but for those who don't prefer they can just read over them. You'll want refer back to this book again and again. It's that good.jazz
As with all new books, I opened to see a page or two, and I couldn't put it down. In the beginning, authors describe what it's like to live with injured boundries, and all I could utter was 'I know, right?!!' To anyone who wants to learn how to take your power back and be in full charge of your life regardless of actions of others or circumstances life throws at you, I highly HIGHLY recommend this book. For years I have been searching for answers that are found on the pages of this book. Countless friends, coworkers, councelors, therapists, and other books don't hold a candle to this best seller. This is a life changer, and I am so grateful that a still small voice miraculously lead me to it. After decades of abuse and mental/emotional enslavement, my life was all about anticipating needs of everyone around me and fulfilling whatever others wanted. Now that my higher power has brought me out of my version of slavery two years ago, I guess I was ready to learn this. Read it, pass it on. If you are stressed beyond measure, timid, or live for others, this is the best investment in your well being other then learning from divine truth dot cm. I just know it will be a blessing. Say good bye to your old self 🙂arosen14
8. Deep Work: Rules For Focused Success In A Distracted World [Book]
Product Details:
Deep work : hardback : grand central publishing : 9781455586691 : 1455586692 : 05 jan 2016 : deep work is the ability to focus without distraction on a cognitively demanding task. it's a skill that allows you to quickly master complicated information and produce better results in less time. in this book, newport flips the narrative on impact in a connected age. instead of arguing distraction is bad, he instead celebrates the power of its opposite. dividing this book into two parts, he first makes the case that in almost any profession, cultivating a deep work ethic will produce massive benefits. he then presents a rigorous training regimen, presented as a series of four rules, for transforming your mind and habits to support this skill.
Reviews:
The concepts explained in this book are so relevant and logical. It is such a challenge to get out of the 'shallow work' we are faced with throughout our days and into the 'deep' but this book spells out how and shows you the benefits that will flow. I read this book in record time and started implementing the concepts immediately.Darren in the Deep
Life changing !!! I'm off social media, retraining my brain to concentrate, workplace productivity has gone through the roof and i am enjoying my work a whole lot more. I gave a copy to my boss hoping she'll encourage deep work practices in our team.bonsaimatt42
Another book recommended to me by a friend. Being a researcher by trade, Deep Work reminds me of the importance of my role – the ability o do sustained and concentrative work. This book goes through the reasons why most of us are transforming our work lives from deep to shallow work. As Cal Newport states – Shallow Work stops us from getting fired; Deep Work gets us promoted. A great book for anyone wondering why they aren't achieving their desired outputs and how to find more value to get to the next desired levelAngela
9. Reinforcement Learning: Industrial Applications Of Intelligent Agents [Book]
Product Details:
Reinforcement learning (rl) will deliver one of the biggest breakthroughs in ai over the next decade, enabling algorithms to learn from their environment to achieve arbitrary goals. this exciting development avoids constraints found in traditional machine learning (ml) algorithms. this practical book shows data science and ai professionals how to learn by reinforcement and enable a machine to learn by itself. author phil winder of winder research covers everything from basic building blocks to state-of-the-art practices. you'll explore the current state of rl, focus on industrial applications, learn numerous algorithms, and benefit from dedicated chapters on deploying rl solutions to production. this is no cookbook; doesn't shy away from math and expects familiarity with ml. learn what rl is and how the algorithms help solve problems become grounded in rl fundamentals including markov decision processes, dynamic programming, and temporal difference learning dive deep into a range of value and policy gradient methods apply advanced rl solutions such as meta learning, hierarchical learning, multi-agent, and imitation learning understand cutting-edge deep rl algorithms including rainbow, ppo, td3, sac, and more get practical examples through the accompanying website
10. Deep Learning With R, Second Edition [Book]
Product Details:
Deep learning from the ground up using r and the powerful keras library! in deep learning with r, second edition you will learn: deep learning from first principles image classification and image segmentation time series forecasting text classification and machine translation text generation, neural style transfer, and image generation deep learning with r, second edition shows you how to put deep learning into action. it’s based on the revised new edition of françois chollet’s bestselling deep learning with python. all code and examples have been expertly translated to the r language by tomasz kalinowski, who maintains the keras and tensorflow r packages at rstudio. novices and experienced ml practitioners will love the expert insights, practical techniques, and important theory for building neural networks. purchase of the print book includes a free ebook in pdf, kindle, and epub formats from manning publications. about the technology deep learning has become essential knowledge for data scientists, researchers, and software developers. the r language apis for keras and tensorflow put deep learning within reach for all r users, even if they have no experience with advanced machine learning or neural networks. this book shows you how to get started on core dl tasks like computer vision, natural language processing, and more using r. about the book deep learning with r, second edition is a hands-on guide to deep learning using the r language. as you move through this book, you’ll quickly lock in the foundational ideas of deep learning. the intuitive explanations, crisp illustrations, and clear examples guide you through core dl skills like image processing and text manipulation, and even advanced features like transformers. this revised and expanded new edition is adapted from deep learning with python, second edition by françois chollet, the creator of the keras library. what's inside image classification and image segmentation time series forecasting text classification and machine translation text generation, neural style transfer, and image generation about the reader for readers with intermediate r skills. no previous experience with keras, tensorflow, or deep learning is required. about the author françois chollet is a software engineer at google and creator of keras. tomasz kalinowski is a software engineer at rstudio and maintainer of the keras and tensorflow r packages. allaire is the founder of rstudio, and the author of the first edition of this book. table of contents 1 what is deep learning? 2 the mathematical building blocks of neural networks 3 introduction to keras and tensorflow 4 getting started with neural networks: classification and regression 5 fundamentals of machine learning 6 the universal workflow of machine learning 7 working with keras: a deep dive 8 introduction to deep learning for computer vision 9 advanced deep learning for computer vision 10 deep learning for time series 11 deep learning for text 12 generative deep learning 13 best practices for the real world 14 conclusions
Reviews:
One of the best textbooks on NNs I have found. I had started a number of others and I accidentally ran into the present one when I was searching for clarification online. When I started reading its context, I stopped the previous one.Petros B
Interesting and usefull for my work
This is an excellent book because it presents clear concepts and code useful to start real applications of deep learning.Laerte Sodré J
11. Learning How To Learn: How To Succeed In School Without Spending All Your Time Studying; A Guide For Kids And Teens [Book]
Product Details:
A surprisingly simple way for students to master any subject–based on one of the world's most popular online courses and the bestselling book a mind for numbers – a mind for numbers and its wildly popular online companion course "learning how to learn" have empowered more than two million learners of all ages from around the world to master subjects that they once struggled with. fans often wish they'd discovered these learning strategies earlier and ask how they can help their kids master these skills as well. now in this new book for kids and teens, the authors reveal how to make the most of time spent studying. this book explains:why sometimes letting your mind wander is an important part of the learning process – how to avoid "rut think" in order to think outside the box – why having a poor memory can be a good thing – the value of metaphors in developing understanding – a simple, yet powerful, way to stop procrastinating – filled with illustrations, application questions, and exercises, this book makes learning easy and fun.
Reviews:
It provides a different perspective on how to organize and learn material for immediate and the long term.ubookie68
I bought this to help me learn how to study better, and I am glad I did. Worth it!Jenny B
I purchased this book because I have to teach myself a topic for my job and wanted insight on how to retain what Im studying. Its written on a young adult level so the concepts are broken down so that anyone can understand. She also has a practice exercise after each chapter to reinforce what was studied. Also, her story about how she came to write this book was very interesting and I think a lot of people feel the same way she did about learning.CYNTHIA
12. Dare To Lead: Brave Work. Tough Conversations. Whole Hearts. [Book]
Product Details:
#1 new york times bestseller – brené brown has taught us what it means to dare greatly, rise strong, and brave the wilderness. named one of the best books of the year by bloomberg leadership is not about titles, status, and wielding power. a leader is anyone who takes responsibility for recognizing the potential in people and ideas, and has the courage to develop that potential. but daring leadership in a culture defined by scarcity, fear, and uncertainty requires skill-building around traits that are deeply and uniquely human. empathy, connection, and courage, to start. four-time #1 new york times bestselling author brené brown has spent the past two decades studying the emotions and experiences that give meaning to our lives, and the past seven years working with transformative leaders and teams spanning the globe. she found that leaders in organizations ranging from small entrepreneurial startups and family-owned businesses to nonprofits, civic organizations, and fortune 50 companies all ask the same question: how do you cultivate braver, more daring leaders, and how do you embed the value of courage in your culture? in this new book, brown uses research, stories, and examples to answer these questions in the no-bs style that millions of readers have come to expect and love. brown writes, “one of the most important findings of my career is that daring leadership is a collection of four skill sets that are 100 percent teachable, observable, and measurable. it’s learning and unlearning that requires brave work, tough conversations, and showing up with your whole heart. easy? no. because choosing courage over comfort is not always our default. worth it? always. whether you’ve read daring greatly and rising strong or you’re new to brené brown’s work, this book is for anyone who wants to step up and into brave leadership.
Reviews:
As always, Brene Brown opens up your heart and guides your good intentions with this book. Very inspiring and a highly satisfying read.The Knowledge Queen
I haven't read any of her other work. I bought this for a workplace book club where we read parts at a time, but naturally I've read the whole thing. I'll reread the parts as we get to them. The advice and lessons in the book are relevant, if you like self reflection. I'm on somewhat of a leadership discovery journey, and this fit into my self sought learning for the month.SHANNON
Full of well researched content and actionable ideas. If you are wanting to make a positive impact in the work you a do by enabling people to show up and be at their best. This book will be your bibleBlue Chip Minds
13. Mindset: The New Psychology Of Success [Book]
Product Details:
From the renowned psychologist who introduced the world to “growth mindset” comes this updated edition of the million-copy bestseller—featuring transformative insights into redefining success, building lifelong resilience, and supercharging self-improvement.“ after decades of research, world-renowned stanford university psychologist carol s. dweck, ph.d., discovered a simple but groundbreaking idea: the power of mindset. people with a fixed mindset—those who believe that abilities are fixed—are less likely to flourish than those with a growth mindset—those who believe that abilities can be developed. mindset reveals how great parents, teachers, managers, and athletes can put this idea to use to foster outstanding accomplishment. in this edition, dweck offers new insights into her now famous and broadly embraced concept. she introduces a phenomenon she calls false growth mindset and guides people toward adopting a deeper, truer growth mindset. she also expands the mindset concept beyond the individual, applying it to the cultures of groups and organizations. with the right mindset, you can motivate those you lead, teach, and love—to transform their lives and your own.
Reviews:
This book clearly explains how you can improve all areas of your life and relationships by implementing the strategies of a growth mindset and the opposite outcome that results from holding on to a fixed mindset. Presented in an upbeat, positive and humorous way. Success is yours for the taking. It's a choice.Ivy
Interesting discussion of the difference bewteen fixed and growth mindsets. Lots of research and stories to back-up the concepts. Good read, especially geared towards teachers, parents and coaches.ROBERT
Holy moly—this book is AMAZING. I'm blown away by how life-altering this book has been. It is loaded with helpful content, and it's such a breeze to read! I flipped through this book so quickly because it's just that good. Super affordable and so worth it! I would highly recommend this book for any professional, but especially for teachers like myself who will be working with and teaching young people the positives of a growth mindset!meg.p
14. Make It Stick: The Science Of Successful Learning [Book]
Product Details:
To most of us, learning something "the hard way" implies wasted time and effort. make it stick turns fashionable ideas like these on their head. drawing on recent discoveries in cognitive psychology and other disciplines, the authors offer concrete techniques for becoming more productive learners.memory plays a central role in our ability to carry out complex cognitive tasks, such as applying knowledge to problems never before encountered and drawing inferences from facts already known. grappling with the impediments that make learning challenging leads both to more complex mastery and better retention of what was learned.many common study habits and practice routines turn out to be counterproductive. underlining and highlighting, rereading, cramming, and single-minded repetition of new skills create the illusion of mastery, but gains fade quickly. more complex and durable learning come from self-testing, introducing certain difficulties in practice, waiting to re-study new material until a little forgetting has set in, and interleaving the practice of one skill or topic with another. speaking most urgently to students, teachers, trainers, and athletes, make it stick will appeal to all those interested in the challenge of lifelong learning and self-improvement.
Reviews:
Fantastic product and real learning tool. I wld say it is 'revolutionery'. Have bought it for grandson's who are studying.Terry O.
Good to learn how to studymad max
Love it, bought for my professional practice. Very useful and helpful.It is very hard to find a book that allows you to understand how you can implement CPD into topic specific classroom practice. Many times I have sat through CPD sessions wondering how I could use this in my lessons. This book has allowed me to do this. I have been able to relate and implement into my professional practice.holzafer
15. The Power Of Habit: Why We Do What We Do In Life And Business [Book]
Product Details:
Over 60 weeks on the new york times bestseller listwith a new afterword by the author – in the power of habit, pulitzer prize–winning business reporter charles duhigg takes us to the thrilling edge of scientific discoveries that explain why habits exist and how they can be changed. distilling vast amounts of information into engrossing narratives that take us from the boardrooms of procter & gamble to sidelines of the nfl to the front lines of the civil rights movement, duhigg presents a whole new understanding of human nature and its potential. at its core,the power of habit contains an exhilarating argument: the key to exercising regularly, losing weight, being more productive, and achieving success is understanding how habits work. – new york times bestseller – npr bestseller – washington post bestseller – los angeles times bestseller – usa today bestseller – publishers weekly bestsellernamed one of the best books of the year bythe wall street journal – financial times“sharp, provocative, and useful.”—jim collins“few [books] become essential manuals for business and living. the power of habitis an exception. charles duhigg not only explains how habits are formed but how to kick bad ones and hang on to the good.”—financial times“a flat-out great read.”—david allen, bestselling author of getting things done: the art of stress-free productivity“you'll never look at yourself, your organization, or your world quite the same way.”—daniel h. – drive and a whole new mind“entertaining . . . enjoyable . . . fascinating . . . a serious look at the science of habit formation and change.”—the new york times book review“cue: see cover. routine: read book. reward: fully comprehend the art of manipulation.”—bloomberg businessweek“absolutely fascinating.”—wired“a fresh examination of how routine behaviors take hold and whether they are susceptible to change . . . the stories that duhigg has knitted together are all fascinating in their own right, but take on an added dimension when wedded to his examination of habits.”— associated press“there's been a lot of research over the past several years about how our habits shape us, and this work is beautifully described in the new book – the power of habit.”—david brooks, the new york times“a first-rate book—based on an impressive mass of research, written in a lively style and providing just the right balance of intellectual seriousness with practical advice on how to break our bad habits.”—the economist“i have been spinning like a top since reading the power of habit, new york times journalist charles duhigg's fascinating best-seller about how people, businesses and organizations develop the positive routines that make them productive—and happy.”—the washington post
Reviews:
For years I felt my organizational habits and routines were a mild case of obsessive compulsive behavior. Although the same habits directly contributed to my profe success, I tried to hide them. This book explains clearly how important those habits and routines are in all areas. I am very glad I read it. Highly recommend!cidinv
I mainly give this book 4 stars because of how it engaged me in the tales of certain companies and studies. I feel it falls a little short in giving detailed advice to change habits.PATRICK
This was a great book, hard to put down. It explains how we do so much of what we do. I even bought another copy to give my son. It wasn't my intention when I started reading, but now I am using the ideas to work on not being so much of a workaholic.gunny-sloan
16. Reinforcement Learning [Book]
Product Details:
Reinforcement learning is the learning of a mapping from situations to actions so as to maximize a scalar reward or reinforcement signal. the learner is not told which action to take, as in most forms of machine learning, but instead must discover which actions yield the highest reward by trying them. in the most interesting and challenging cases, actions may affect not only the immediate reward, but also the next situation, and through that all subsequent rewards. these two characteristics — trial-and-error search and delayed reward — are the most important distinguishing features of reinforcement learning. reinforcement learning is both a new and a very old topic in ai. the term appears to have been coined by minsk (1961), and independently in control theory by walz and fu (1965). the earliest machine learning research now viewed as directly relevant was samuel's (1959) checker player, which used temporal-difference learning to manage delayed reward much as it is used today. of course learning and reinforcement have been studied in psychology for almost a century, and that work has had a very strong impact on the ai/engineering work. one could in fact consider all of reinforcement learning to be simply the reverse engineering of certain psychological learning processes (e.g. operant conditioning and secondary reinforcement). reinforcement learning is an edited volume of original research, comprising seven invited contributions by leading researchers.
Specifications:
Language |
English |
Release Date |
October 2012 |
Length |
172 Pages |
Dimensions |
0.4" x 6.1" x 9.2" |
Age Range |
18 years and up |
Grade Range |
Postsecondary and higher |
Reviews:
Nicely packaged and arrived right on time.us_rubay
17. Reinforcement Learning [Book]
Product Details:
Reinforcement learning is the learning of a mapping from situations to actions so as to maximize a scalar reward or reinforcement signal. the learner is not told which action to take, as in most forms of machine learning, but instead must discover which actions yield the highest reward by trying them. in the most interesting and challenging cases, actions may affect not only the immediate reward, but also the next situation, and through that all subsequent rewards. these two characteristics — trial-and-error search and delayed reward — are the most important distinguishing features of reinforcement learning. reinforcement learning is both a new and a very old topic in ai. the term appears to have been coined by minsk (1961), and independently in control theory by walz and fu (1965). the earliest machine learning research now viewed as directly relevant was samuel's (1959) checker player, which used temporal-difference learning to manage delayed reward much as it is used today. of course learning and reinforcement have been studied in psychology for almost a century, and that work has had a very strong impact on the ai/engineering work. one could in fact consider all of reinforcement learning to be simply the reverse engineering of certain psychological learning processes (e.g. operant conditioning and secondary reinforcement). reinforcement learning is an edited volume of original research, comprising seven invited contributions by leading researchers.
Specifications:
Language |
English |
Release Date |
October 2012 |
Length |
172 Pages |
Dimensions |
0.4" x 6.1" x 9.2" |
Age Range |
18 years and up |
Grade Range |
Postsecondary and higher |
Reviews:
Nicely packaged and arrived right on time.us_rubay
18. An Introduction To Deep Reinforcement Learning [Book]
Product Details:
Deep reinforcement learning is the combination of reinforcement learning (rl) and deep learning. this field of research has recently been able to solve a wide range of complex decision-making tasks that were previously out of reach for a machine. deep rl opens up many new applications in domains such as healthcare, robotics, smart grids, finance, and many more. this book provides the reader with a starting point for understanding the topic. although written at a research level it provides a comprehensive and accessible introduction to deep reinforcement learning models, algorithms and techniques. particular focus is on the aspects related to generalization and how deep rl can be used for practical applications. written by recognized experts, this book is an important introduction to deep reinforcement learning for practitioners, researchers and students alike.
Specifications:
Language |
English |
Release Date |
March 2019 |
Length |
156 Pages |
Dimensions |
0.3" x 6.1" x 9.2" |
19. Reinforcement Learning For Finance: Solve Problems In Finance With Cnn And Rnn Using The Tensorflow Library [Book]
Product Details:
This book introduces reinforcement learning with mathematical theory and practical examples from quantitative finance using the tensorflow library. – reinforcement learning for finance begins by describing methods for training neural networks. next, it discusses cnn and rnn – two kinds of neural networks used as deep learning networks in reinforcement learning. further, the book dives into reinforcement learning theory, explaining the markov decision process, value function, policy, and policy gradients, with their mathematical formulations and learning algorithms. it covers recent reinforcement learning algorithms from double deep-q networks to twin-delayed deep deterministic policy gradients and generative adversarial networks with examples using the tensorflow python library. it also serves as a quick hands-on guide to tensorflow programming, covering concepts ranging from variables and graphs to automatic differentiation, layers, models, and loss functions. – after completing this book, you will understand reinforcement learning with deep q and generative adversarial networks using the tensorflow library. – what you will learn – understand the fundamentals of reinforcement learning – apply reinforcement learning programming techniques to solve quantitative-finance problems – gain insight into convolutional neural networks and recurrent neural networks – understand the markov decision process – who this book is for – data scientists, machine learning engineers and python programmers who want to apply reinforcement learning to solve problems.
Reviews:
Well written and explained book with algorithm implementationSam
20. Reinforcement Learning For Finance: Solve Problems In Finance With Cnn And Rnn Using The Tensorflow Library [Book]
Product Details:
This book introduces reinforcement learning with mathematical theory and practical examples from quantitative finance using the tensorflow library. – reinforcement learning for finance begins by describing methods for training neural networks. next, it discusses cnn and rnn – two kinds of neural networks used as deep learning networks in reinforcement learning. further, the book dives into reinforcement learning theory, explaining the markov decision process, value function, policy, and policy gradients, with their mathematical formulations and learning algorithms. it covers recent reinforcement learning algorithms from double deep-q networks to twin-delayed deep deterministic policy gradients and generative adversarial networks with examples using the tensorflow python library. it also serves as a quick hands-on guide to tensorflow programming, covering concepts ranging from variables and graphs to automatic differentiation, layers, models, and loss functions. – after completing this book, you will understand reinforcement learning with deep q and generative adversarial networks using the tensorflow library. – what you will learn – understand the fundamentals of reinforcement learning – apply reinforcement learning programming techniques to solve quantitative-finance problems – gain insight into convolutional neural networks and recurrent neural networks – understand the markov decision process – who this book is for – data scientists, machine learning engineers and python programmers who want to apply reinforcement learning to solve problems.
Reviews:
Well written and explained book with algorithm implementationSam