Step-by-step implementation of data science tools and algorithms for hands-on learning
Covers Python basics, linear algebra, statistics, and probability to build foundational skills
Includes machine learning modules such as linear regression, decision trees, and neural networks for practical application
Explores real-world data analysis techniques including data cleaning, visualization, and recommendation systems
Guidance on using Python libraries for data science tasks, ensuring readers can apply concepts in practice
Summarized by Shop
Data science libraries, frameworks, modules, and toolkits are great for doing data science, but they’re also a good way to dive into the discipline without actually understanding data science. In this book, you’ll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch. If you have an