Top 5 books for data science using python

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Top 5 books for data science using python

·  “Python Machine Learning” by Sebastian Raschka and Vahid Mirjalili: This book is a comprehensive introduction to machine learning using Python. It covers a wide range of topics, including supervised and unsupervised learning, deep learning, and natural language processing. It is written for both beginners and experienced data scientists, and includes practical examples and code snippets to help readers understand the concepts.

·  “Python Data Science Handbook” by Jake VanderPlas: This book is a comprehensive guide to data science using Python. It covers a wide range of topics, including data manipulation, data visualization, and machine learning. It is written for both beginners and experienced data scientists, and includes practical examples and code snippets to help readers understand the concepts.

·  “Introduction to Machine Learning with Python” by Andreas Müller and Sarah Guido: This book is a comprehensive introduction to machine learning using Python. It covers a wide range of topics, including supervised and unsupervised learning, deep learning, and natural language processing. It is written for both beginners and experienced data scientists, and includes practical examples and code snippets to help readers understand the concepts.

·  “Data Science from Scratch” by Joel Grus: This book is a comprehensive introduction to data science for beginners using Python. It covers a wide range of topics, including probability and statistics, linear algebra, and machine learning. It is written in a clear and accessible style, and includes practical examples and code snippets to help readers understand the concepts.

·  “Data Wrangling with Python” by Jacqueline Kazil and Katharine Jarmul: This book is a comprehensive guide to data wrangling using Python. It covers a wide range of topics, including data cleaning, data exploration, and data visualization. It is written for both beginners and experienced data scientists, and includes practical examples and code snippets to help readers understand the concepts.

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