Implementing machine learning programmatically!

I finally started programming simple algorithms such as linear regression and decision trees. I was able to use all of my previously gained knowledge about the theory behind machine learning and its different algorithms. Furthermore, I was able to utilize my knowledge of the steps that take place in machine learning projects and went step by step to create a model with the help of some outside sources. This helped me gain some practical knowledge of machine learning and helped me problem-solve for problems and obstacles that came in my way when starting programming. I was able to get more familiar with platforms such as TensorFlow and Jupyter Notebook during the process of creating these simple models. I hope to transition into more real-world problems before I get to implement neural networks programmatically in order to problem-solve and create solutions by myself.

Now, I hope to transition into neural networks and the various types of deep learning that could help me accomplish my goal of creating computer vision and natural language processing. This will also help me add to my original work and thus, help me gain a better understanding of what I can create as my final product in the future. So see you next week, same place, same time.