Data science is a rapidly growing field that requires a strong understanding of various technologies and techniques. Online technical books are an excellent resource for data scientists, providing detailed explanations and examples of the latest techniques and technologies. Here are some of the best online technical books for data scientists:
"Python for Data Analysis" by Wes McKinney: This book provides a comprehensive introduction to data analysis using Python and is a must-read for any data scientist.
"Data Science from Scratch" by Joel Grus: This book provides a comprehensive introduction to data science, covering the basics of statistics, programming, and data analysis.
"Introduction to Machine Learning with Python" by Andreas Müller and Sarah Guido: This book is a beginner-friendly guide to machine learning with Python, covering a wide range of techniques and algorithms.
"Deep Learning" by Yoshua Bengio, Ian Goodfellow, and Aaron Courville: This book provides a comprehensive introduction to deep learning, covering the latest techniques and technologies in the field.
"Data Science for Business" by Foster Provost and Tom Fawcett: This book provides a comprehensive introduction to data science, specifically tailored for business professionals.
"Python Machine Learning" by Sebastian Raschka and Vahid Mirjalili: This book is a comprehensive guide to machine learning with Python, covering a wide range of techniques and algorithms.
"Big Data: A Revolution That Will Transform How We Live, Work, and Think" by Viktor Mayer-Schönberger: This book provides an overview of big data and its potential impact on society, including the latest technologies and techniques.
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