Phase 1 — Python & Math
April 27, 2026
Continue learning Mathematics for ML and Python crash course
What I Did
- Completed week 3 of the linear algebra part in Mathematics for ML
- Implemented a Neural Network with numpy and trained it to work on a set of data and predict outcomes
What I Learned
- Learned about Vectors and Linear Transformations
- Learned how a Neural Network is a large collection of linear models
- Watched 3Blue1Brown video on machine learning(eye opening man...)
- Learned about cost function, activation function, perceptron(things are starting to get real interesting...)
Bugs & Blockers
- None
Concepts That Need More Time
- N/A
Tomorrow
- Complete week 4 of the Mathematics for ML(Linear Algebra)
- Continue reading my Python crash course book(I only need to do the project part)
- Found a new book called Think Python which I might try to explore and see things I can learn from there
Wins
- Implemented a simple Neural Network
- I started reading the book named Deep Work by Cal Newport and I'm already past page 25 on the first day