Machine Learning Roadmap 2022
Step 1: Prefer your programming language Like Python And R.
I suggest Python because it is a popular language and easy to learn ,We can switch Domain Easily.
Python offers popular frameworks like Django ,Flask for Backend development, Tkinter for GUI development. If you go with python, you must learn sklearn for Machine Learning.
It has a lot of useful classes for preprocessing your data for further analysis and also learn TensorFlow Module, which can help you build a neural network. here are some free resources to learn python 👉 here
Step 2: Linear Algebra
If you want to master in Machine Learning you should learn Linear Algebra, this is essential to build ML models and also learn ml in depth. here is some recourses to linear Algebra 👉 here
Step 3: Learn Statistics
We require basic knowledge of probability and statistics to master in machine learning. here are some resources to learn statistics 👉 here
Step 4: Learn Core ML Algorithms
Just start with ml algorithms
* Supervised and unsupervised learning
Step 5:Python Libraries
Step 6: Learn Deployment
To Organize our ML Models with a backend , you need to learn frameworks like Django and Flask, and also to deploy the model Kubernetes and Docker is the very helpful if you want to deploy your models.