{"id":12449,"date":"2024-01-02T02:39:30","date_gmt":"2024-01-02T02:39:30","guid":{"rendered":"https:\/\/lacountystore.com\/\/?p=12449"},"modified":"2024-01-02T02:39:30","modified_gmt":"2024-01-02T02:39:30","slug":"best-books-for-data-science","status":"publish","type":"post","link":"https:\/\/lacountystore.com\/best-books-for-data-science\/","title":{"rendered":"20 Best Books For Data Science (2024 Update)"},"content":{"rendered":"

Are you looking for the Best Books For Data Science<\/strong>? If so, you’ve come to the right place.<\/p>\n

Choosing the Best Books For Data Science can be difficult as there are so many considerations, such as Funko, Hasbro, LEGO, Melissa & Doug, Penguin Random House, WHSmith, Amazon.com. We have done a lot of research to find the Top 20 Best Books For Data Science<\/strong> available.<\/p>\n

The average cost is $38.16<\/i>. Sold comparable range in price from a low of $8.80<\/i> to a high of $93.81<\/i>.<\/p>\n

Based on the research we did, we think R for Data Science: Import, Tidy, Transform, Visualize, and Model Data [Book]<\/strong><\/a> 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.<\/p>\n

20 Best Books For Data Science (18 Sellers)<\/h2>\n
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Product Image<\/span><\/th>\nProduct Name<\/span><\/th>\nFeatures<\/span><\/th>\nCheck Price<\/span><\/th>\n<\/tr>\n<\/thead>\n
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    • Wrangle-transform your datasets into a form convenient for analysis<\/li>\n
    • Program-learn powerful r tools for solving data problems with greater clarity and ease<\/li>\n
    • Explore-examine your data, generate hypotheses, and quickly test them<\/li>\n<\/ul>\n<\/div>\n<\/div>\n<\/li>\n<\/ul>\n<\/div>\n<\/td>\n
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    • Data science and statistical analysis for the business professional<\/li>\n
    • Numerous instantly familiar real-world use cases<\/li>\n
    • Keys to effective data presentations<\/li>\n<\/ul>\n<\/div>\n<\/div>\n<\/li>\n<\/ul>\n<\/div>\n<\/td>\n
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    • To clarify, this is the solutions manual, not the textbook.<\/li>\n
    • You get immediate access to download your solutions manual.<\/li>\n
    • You will receive a complete solutions manual; in other words, all chapters will be there.<\/li>\n<\/ul>\n<\/div>\n<\/div>\n<\/li>\n<\/ul>\n<\/div>\n<\/td>\n
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    • Py, pandas, matplotlib, scikit-learn, and other related tools.<\/li>\n
    • Pandas: features the data.<\/li>\n
    • Frame for efficient storage and manipulation of labeled\/columnar data in python.<\/li>\n<\/ul>\n<\/div>\n<\/div>\n<\/li>\n<\/ul>\n<\/div>\n<\/td>\n
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    • Description\\n\\n<\/li>\n
    • Kelleher, brendan tierney isbn: 0262535432,9780262535434\\n\\n<\/li>\n
    • Related\\n\\n<\/li>\n<\/ul>\n<\/div>\n<\/div>\n<\/li>\n<\/ul>\n<\/div>\n<\/td>\n
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    • Understand how data science fits in your organization–and how you can use it for competitive advantage<\/li>\n
    • Treat data as a business asset that requires careful investment if you&#39;re to gain real value<\/li>\n
    • Approach business problems data-analytically, using the data-mining process to gather good data in the most appropriate way<\/li>\n<\/ul>\n<\/div>\n<\/div>\n<\/li>\n<\/ul>\n<\/div>\n<\/td>\n
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    • Understand how data science fits in your organization–and how you can use it for competitive advantage<\/li>\n
    • Treat data as a business asset that requires careful investment if you&#39;re to gain real value<\/li>\n
    • Approach business problems data-analytically, using the data-mining process to gather good data in the most appropriate way<\/li>\n<\/ul>\n<\/div>\n<\/div>\n<\/li>\n<\/ul>\n<\/div>\n<\/td>\n
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    • Contains war stories, offering perspectives on how data science applies in the real world<\/li>\n
    • Includes homework problems, providing a wide range of exercises and projects for self-study<\/li>\n
    • Provides take-home lessons, emphasizing the big-picture concepts to learn from each chapter<\/li>\n<\/ul>\n<\/div>\n<\/div>\n<\/li>\n<\/ul>\n<\/div>\n<\/td>\n
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    • You get immediate access to download your test bank.<\/li>\n
    • To clarify, this is the test bank, not the textbook.<\/li>\n
    • You will receive a complete test bank; in other words, all chapters will be there.<\/li>\n<\/ul>\n<\/div>\n<\/div>\n<\/li>\n<\/ul>\n<\/div>\n<\/td>\n
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    • Binding type: paperback<\/li>\n
    • Year published: 2017-03-24<\/li>\n
    • Number of pages: 146<\/li>\n<\/ul>\n<\/div>\n<\/div>\n<\/li>\n<\/ul>\n<\/div>\n<\/td>\n
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    • Binding type: paperback<\/li>\n
    • Year published: 2022-08-16<\/li>\n
    • Number of pages: 325<\/li>\n<\/ul>\n<\/div>\n<\/div>\n<\/li>\n<\/ul>\n<\/div>\n<\/td>\n
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    • Think statistically and understand the role variation plays in your life and decision making<\/li>\n
    • Speak intelligently and ask the right questions about the statistics and results you encounter in the workplace<\/li>\n
    • Understand what&#39;s really going on with machine learning, text analytics, deep learning, and artificial intelligence<\/li>\n<\/ul>\n<\/div>\n<\/div>\n<\/li>\n<\/ul>\n<\/div>\n<\/td>\n
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    • To clarify, this is the solutions manual, not the textbook.<\/li>\n
    • You get immediate access to download your solutions manual.<\/li>\n
    • You will receive a complete solutions manual; in other words, all chapters will be there.<\/li>\n<\/ul>\n<\/div>\n<\/div>\n<\/li>\n<\/ul>\n<\/div>\n<\/td>\n
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    • Statistical inference, exploratory data analysis, and the data science process<\/li>\n
    • Spam filters, naive bayes, and data wrangling<\/li>\n
    • Logistic regression<\/li>\n<\/ul>\n<\/div>\n<\/div>\n<\/li>\n<\/ul>\n<\/div>\n<\/td>\n
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    • The fast and easy way to learn python programming and statistics<\/li>\n
    • Get started with data science and python<\/li>\n
    • Visualize information<\/li>\n<\/ul>\n<\/div>\n<\/div>\n<\/li>\n<\/ul>\n<\/div>\n<\/td>\n
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    • Binding type: paperback<\/li>\n
    • Year published: 2022-03-01<\/li>\n
    • Number of pages: 200<\/li>\n<\/ul>\n<\/div>\n<\/div>\n<\/li>\n<\/ul>\n<\/div>\n<\/td>\n
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    • Data science for the business professional<\/li>\n
    • Statistical analysis using the r language<\/li>\n
    • Numerous instantly familiar use cases<\/li>\n<\/ul>\n<\/div>\n<\/div>\n<\/li>\n<\/ul>\n<\/div>\n<\/td>\n
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    • Data science for the business professional<\/li>\n
    • Statistical analysis using the r language<\/li>\n
    • Numerous instantly familiar use cases<\/li>\n<\/ul>\n<\/div>\n<\/div>\n<\/li>\n<\/ul>\n<\/div>\n<\/td>\n
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    • Binding type: paperback<\/li>\n
    • Year published: 2017-05-05<\/li>\n
    • Number of pages: 328<\/li>\n<\/ul>\n<\/div>\n<\/div>\n<\/li>\n<\/ul>\n<\/div>\n<\/td>\n
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    • Provides a background in big data and data engineering before moving on to data science and how it&#39;s applied to generate value.<\/li>\n
    • Includes coverage of big data frameworks like hadoop, mapreduce, spark, mpp platforms, and nosql.<\/li>\n
    • And more…<\/li>\n<\/ul>\n<\/div>\n<\/div>\n<\/li>\n<\/ul>\n<\/div>\n<\/td>\n
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