This week, I continued on Machine Learning Mathematics and I learnt more about Git.
ML Mathematics
I feel like the course actually gets easier as you progress through it. I learnt that turning any matrix into an orthogonal (90 degrees to each other) matrix is always a good idea. It's basically to make it possible to use dot product with it and changing basis vectors, etc. It's also simple to turn any matrices into orthogonal matrices, using a process called the Gram Schmidt process.
Git
Learnt some more basic concepts such as branching, merging and using remote repositories like Github. I also learnt about rebasing a branch that is off the master branch to make the commit history more linear.
Wrap-up
To be honest, this week isn't impressive and I feel like I should've accomplished more. Next week, I'll finish both the introduction to Git and the first course in ML Mathematics, and I'm going to start learning data visualization with Python as well as starting a machine learning course. Thanks for reading.
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