Repository is designed with a goal of in-depth understanding of Machine Learning models

My vision:

1) Implementing algorithms from scratch using NumPy, instead of simply importing them from TensorFlow and scikit-learn

2) Developing a strong mathematical understanding of how these algorithms work, alongside practicing Linear Algebra through applied learning using the book: (https://mml-book.github.io/book/mml-book.pdf)

• Mathematics for Machine Learning

3) The current focus is on optimizing the cost function using Gradient Descent and partial derivatives

4) Visualizing key concepts for easier understanding

5) Apart from everything mentioned, practicing and reinforcing Python skills alongside, such as working with classes and data structures