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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
  • 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.

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