Machine Learning - basic course: Encouragement words
Hi, let's begin a nice journey into the Machine Learning world. I like an expression attributed
to the Chinese sage Lao Tzu: "A journey of a thousand miles begins with a single
step". My creed is to do things the right way. Another expression says: "If you want to do things faster,
do it slower". The main focus of this site is to provide a fundamental education in
Reinforcement Learning. It impossible to learn RL without strong understanding ML concepts in general.
This resource is a place where you can master basic knowledge about Machine Learning in details.
RL is important branch of ML, and come together, especially modern
Deep Reinforcement Learning. So, it is enormously important to get the right information in the
right sequential order to move forward.
In this course, we will be focusing on pure Python implementations
of ML algorithms and other ML techniques. We will also use some general
Python packages such as Numpy for Linear Regression and
Matplotlib for visualization. Later on, you will use built-in ML Python
libraries. A real ML engineer should know and understand how it works underhood.
This is necessary if you intend to conduct research or develop production-ready
solutions in the future. This course contains basic
information about ML and other
useful ML practices, which must become a strong foundation for you as an
Artificial Intelligence (AI) engineer.
It's better to implement these algorithms and ideas yourself,
especially from memory, and revisit them periodically. Although it takes more time,
this approach yields a greater long-term benefits speaking in RL terminology.
It won't be fast, but if you make it your daily routine results will come soon.
So, it's time now to take the first step (lesson 1) in this breathtaking ML journey, and we will see where it takes you.