This repo contains the files I used while learning Machine Learning with python. It covers the following:
-
- This includes:
- Linear Regression
- EDA with Pandas
- Data Preprocessing: Missing data, scaling etc
- Cross-Validation.
- This includes:
-
- This includes:
- DecisionTrees
- RandomForest
- GradientBoosting
- Ensemble Methods
- XGBoost and LightGBM
- Text Classfication
- This includes:
-
- This includes:
- K-Means Clustering
- PCA
- DBSCAN, t-SNE, Hiearchical Clustering
- Neural Networks
- API Basics - Flask Endpoints
- This includes:
- This repository contains the projects I have done during my learning journney(Also posted on kaggle):
- Titanic Dataset Project.
- Ames Housing Dataset Project.
- Creditcard Fraud Dataset Project
- Telco Customer Churn Dataset Project.
- Bank Dataset Project.
After learning i worked on 3 other major projects in a different repository:
- Salary Predictor: Predict salaries from job postings (web scraping or existing dataset) — regression + deployment. See more here
- Movie Review Sentiment App: NLP pipeline on IMDB reviews + Flask web app. See more here
- Disease Prediction System: Diabetes or heart disease dataset + ensemble model + Streamlit dashboard. See more here
Note: These projects are separated from the others because of the UI implementation ie they have a front end.