Best Calculus Books to Learn Machine-Learning and AI

Learning calculus is an essential foundation for understanding machine learning, as it is used in many of the algorithms and concepts. Here are some of the best calculus books that can help you learn calculus for machine learning:

1. "Calculus" by James Stewart: This is a comprehensive calculus book that covers all the essential topics. It is an excellent resource for beginners and advanced learners alike.

2. "Calculus: A Complete Course" by Robert A. Adams: This book is also a comprehensive guide to calculus, with a particular emphasis on real-world applications. It includes many examples and exercises related to machine learning.

3. "Multivariable Calculus" by James Stewart: This book focuses on multivariable calculus, which is essential for understanding many machine learning algorithms, such as support vector machines, neural networks, and deep learning.

4. "Linear Algebra and Its Applications" by Gilbert Strang: Although not a calculus book, this textbook covers linear algebra, which is a crucial mathematical tool in machine learning. It includes many real-world applications and examples.

5. "Essential Calculus: Early Transcendentals" by James Stewart: This book is a concise introduction to calculus and is a great resource for beginners who want to learn calculus quickly. It also includes many examples and exercises related to machine learning.

Overall, it is essential to understand calculus to excel in machine learning, and these books are excellent resources for learning the subject.