Hello there.

I have recently decided it would be pretty cool to do machine learning and AI for my career, so I decided to research online on how I could get good at it. I figured since I am basically starting out with pretty much 0 knowledge about any ML topics, it would be fun to write blog posts about my journey on getting good at ML so I can read about it in the future and look back at what I have accomplished.

I saw a lot of cool libraries about machine learning online, such as tensorflow, pytorch, numpy, and others. However, I feel like I should get the fundamentals down before I start using those libraries. The fundamentals for machine learning seems to be alot of calculus, linear algebra, statistics and python, so that is what I will be focusing on doing for the start of me learning ML. I probably don't need to do much to learn python, as I think I am pretty solid when it comes to reading and writing code. However, I know jackshit about any math as I did not pay attention any of the math classes I have taken at school (i regret doing so...). Therefore I will probably spend most of my time starting out reviewing calculus, linear algebra, and statistics.

While searching for resources to learn ML, I found this book called Mathematics for Machine Learning, which seems to be about fundamental mathematical concepts when it comes to understanding ML, so I will be starting with reading this textbook from front to back and doing the exercises. I also found Artificial Intelligence: A Modern Approach. This book is used as the textbook for many introduction to AI courses in university, and was also recommended on a bunch of reddit forums, so I will probably look at that after I finished Mathematics for Machine Learning. After that I will probably google online for more resources.

Thats all I'm writing for this intro post. Gonna open up the Mathematics for Machine Learning pdf doc for the first time now and start reading it. I will most likely be writing a new blog post every week about me learning ML and what I have learned, so see you all in a week :)