As I began my journey into the world of machine learning in python, I was totally lost on what should I do. Machine Learning has been the latest craze in the world of programming and I was eager to step my foot into this newest world in the realm of programming.
AI is set to be the next craze in the next 50 years or so and my curiosity helped me churn out some possible resources I could need to understand this bleak idea to me.
I first came across this link above, in which Andrew Ng (He is awesome by the way) , a very renowned machine learning expert, shares on the mathematical and conceptual logic and understanding of the machine learning algorithms. I found this very educational as it was here I first was able to relate machine learning problems to optimisation.
Hereafter, I went to the Elements of AI course.
In this course, I was able to get a better grasp of the fundamental logic and reasoning behind machine learning algorithms.
I thought now I was ready to dive into the programming part of machine learning. However, the courses I found either only talked about the code with no explanation about the concept or showed the code after explaining the concepts. It was only until I saw this video series by CodeBasics that I was really able to piece things together.
He explained the machine learning algorithms, explained the logic behind each line of code he was writing and what steps he was taking to use the ml model. Shout out to him and to all other beginners out there, I would recommend you to follow him.
After looking at his videos, I thought it was time I began my first ml project. More about it in the next post!