Machine learning Topics

Linear and Logistic Regression
Decision Trees
Random Forests
SVM
Naive Bayes and KNN
K-Means Clustering
Feature Engineering and Dimentionality Reduction
Data Visualization
Data analytics and EDA
Data Cleaning
All basic evaluation metrics and interpretation

Tools/Frameworks

Scikit-Learn
Pytorch basic
Streamlit and Flask
Python, Numpy, Pandas, Matlotlib, Seaborn, Plotly
Deep learning Basics
Docker basics

Want to learn more and grow my skills along the way.