README.md

Still in Progress!! (please don't mind the lack of structure😭)

Data Science Python Repository

Description

This repo contains the files I used while learning Machine Learning with python. It covers the following:

1. Foundations(Regression)

   • This includes:
     1. Linear Regression
     2. EDA with Pandas
     3. Data Preprocessing: Missing data, scaling etc
     4. Cross-Validation.

2. Classification

   • This includes:
     1. DecisionTrees
     2. RandomForest
     3. GradientBoosting
     4. Ensemble Methods
     5. XGBoost and LightGBM
     6. Text Classfication

3. Unsupervised Learning

   • This includes:
     1. K-Means Clustering
     2. PCA
     3. DBSCAN, t-SNE, Hiearchical Clustering
     4. Neural Networks
     5. API Basics - Flask Endpoints

Projects

• This repository contains the projects I have done during my learning journney(Also posted on kaggle):
  1. Titanic Dataset Project.
  2. Ames Housing Dataset Project.
  3. Creditcard Fraud Dataset Project
  4. Telco Customer Churn Dataset Project.
  5. Bank Dataset Project.

After learning i worked on 3 other major projects in a different repository:

1. Salary Predictor: Predict salaries from job postings (web scraping or existing dataset) — regression + deployment. See more here
2. Movie Review Sentiment App: NLP pipeline on IMDB reviews + Flask web app. See more here
3. 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.