When I was doing this project, I was a rising Senior at Clark University, double majoring in Economics and Computer Science and minoring in Data Science. I was fortunate enough to enroll in professor Basye's Data Science 225 - Applied Machine Learning - in the spring semester of my Junior year and it was, no doubt, the coolest class I had taken thus far. During the class, I got to learn about different Machine Learning algorithm, how one should catergorize those algorithms and do many end-to-end realy ML projects. The class used "Hands-On Machine Learning with Scikit-Learn and TensorFlow" - a book by Aurélien Géron. This is a great book to begin your Machine Learning and Deep Learning journey. It explains perfectly how we can employ different ML algorithms via Scikit-learn library. I am interested in how each algorithm actually works instead of just keep using .fit() and . predict() functions in Scikit-learn. That's why this mini project was born.
I will try to build all ML algorithms using only Numpy and Pandas to gain a deeper understanding of what actually going on under the hood.
Each folder will be about one algorithms. Make sure you have all package installed before running the code.
All the credit to Tiep Vu (the author of 'Machine Learning co ban') and Aurélien Geron (the author of Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow). I am only replicating their code (with a few changes) and adding comments along the way for a studying purpose only. I cannot put in words how thankful I am for of their work. Not only do they help me understand ML algorithms better, they also give great visualization techniques.
If you are Vietnamese and you want to learn more about Machine Learning, make sure to check out Tiep's work. Here is the link to his blog "Machine Learning co ban" and the link to his code.
You can also check out Aurélien's book and code here.
Make sure to support both authors by buying the paperback book.