Before Machine Learning Vol 2 - Calculus EBOOK PDF

This book redefines the approach to learning calculus for machine learning. It steers away from traditional, formal methods, opting instead for a story-like, conversational style filled with humor. The aim is to make calculus concepts accessible and engaging, connecting them with real-life applications in machine learning.
 
What You Will Achieve:
 
Practical Understanding:
Apply calculus concepts such as derivatives and limits to real-world machine learning problems.
Understand the mathematical underpinnings of algorithms like linear regression, gradient descent, and neural networks.
 
Enhanced Skills:
Gain deep insights into the workings of optimization algorithms including RMSprop, Momentum, and ADAM.
Master the calculus behind neural network optimization.
 
Solid Foundation:
Develop a robust foundation in calculus, essential for excelling in machine learning.
Equip yourself with the theoretical knowledge and practical skills to advance in your machine learning journey, suitable for both novices and experienced practitioners.
 
Complementary Exercises:
Engage in practical exercises, including coding examples, to reinforce learning.