I would document this as a journey rather than just laying out content. Just an interesting way to go through the whole content and as well as learn something new.
So For the introduction I am a data engineer working in a MNC. I always had interest in the field of Data Science and wanted to do something in the data domain itself. I stumbled upon Data Engineering in this journey and thought to give it a shot, while everyone was chasing behind Data Science - very few people really knew about the domain of data engineering.
Anyways what interested me more was Machine Learning, which actually gives you the control to make changes rather than just randomly using a model and trying to make it better without fully understanding it. Thus the journey to become a Machine Learning Engineer began. (2024)
Basics Of Machine Learning PART I - Probability & Statistics, Linear Algebra and Basic Calculus.
Understanding these topic in depth is not mandatory, But knowing about them surely gives a good edge to us compared to others.
So in the upcoming we will be starting with Probability & Statistics. I will try to keep it short and no bs rule will be applied.
Thank you for your time :)
