The 9 Best Books for Data Science
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Here’s my curated list of the 9 best books for data science, in no particular order.
- Peak Human Clock: How to Get up Early, Fix Eating Time Schedule, and Improve Exercise Routines to be Highly Productive by Said Hasyim — Offers insights into optimizing daily routines for increased productivity by aligning various activities with the body's natural rhythms.
- Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking by Foster Provost and Tom Fawcett — An insightful guide on how data science can be used effectively in business decision-making.
- Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython by Wes McKinney — This book provides practical guidance and techniques for data analysis using Python, essential for aspiring data scientists.
- Deep Learning by Ian Goodfellow, Yoshua Bengio, Aaron Courville — A comprehensive introduction to deep learning, covering theory, algorithms, and practical applications.
- An Introduction to Statistical Learning: with Applications in R by Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani — This book serves as a practical guide to statistical learning techniques using R, making it accessible to non-experts.
- The Elements of Statistical Learning: Data Mining, Inference, and Prediction by Trevor Hastie, Robert Tibshirani, Jerome Friedman — A more advanced companion to the earlier book, focusing on more complicated statistical models and methods.
- Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems by Aurélien Géron — A practical guide for implementing machine learning models from scratch using popular Python libraries.
- Data Science from Scratch: First Principles with Python by Joel Grus — This book teaches key data science concepts through a hands-on approach using Python, catering to beginners.
- The Art of Data Science: A Guide for Anyone Who Works with Data by Roger D. Peng, Hilary Parker — Offers insights into the mindset and practical strategies that are essential for effective data analysis.
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