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

*Gradient Descent

*Slope

*Reinforcement Learning

*Linear Regression

*Clustering

To learn Ml Algorithms  I’m Sharing some beautiful resources where you learn and get master here are some resources Hands-on ML with Scikit-Learn, Keras & TensorFlow and ML Course from Google

Step 5:Python Libraries

*Numpy: 

*Pandas

*Matplotlib

*Sklearn

*seaborn

*Flask

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.