Learning machine learning algorithms!

During the past week, I learned about some of the basic algorithms such as linear regression, simple and multiclass classification, and the cost function in one of my courses that I am currently taking. Moreover, I was able to gain an overall understanding of how these algorithms actually work mathematically. For example, I found out about the different concepts in each of these algorithms and this also connected to my practical knowledge of implementing these algorithms and the knowledge of using regularization to prevent over-fitting. My previous concepts of what the algorithms are supposed to do and why they are supposed to do it connected with this new knowledge of how the algorithms actually work. I also learned how to visualize the problems that use these algorithms in graphs, got information about the concepts inside each algorithm, and solidified my concepts. I still need to learn about neural networks, which I am fascinated to learn, but this has helped me achieve my machine learning foundations that will ultimately help me with my future project/research.

My goal for this week is to dig deeper into the complex algorithms as I am finally gaining a much better understanding of how these algorithms really work. Furthermore, I now feel much more confident to start exploring and programming on Tensorflow with simple machine learning projects. So see you next week, same place, same time.