Machine Learning Portfolio

A comprehensive machine learning portfolio containing foundational exercises, practical projects, and utilities for learning and implementing ML algorithms and models.

📋 Overview

This repository is organized into three main sections:

• Exercises: Foundational ML concepts with interactive Jupyter notebooks
• Projects: Real-world ML applications and case studies
• Common: Shared utilities and helper functions

📚 Exercises - Foundational ML

The exercises/foundation/ directory contains 9 progressively complex Jupyter notebooks covering fundamental machine learning concepts:

#	Notebook	Topics
1	1.0_basic.ipynb	ML basics and fundamentals
2	2.0_linear_regression_&_svm.ipynb	Linear Regression, Support Vector Machines
3	3.0_generalization_&_evaluation_cm.ipynb	Generalization, Evaluation Metrics, Confusion Matrix
4	4.0_neural_network_basic.ipynb	Neural Network Fundamentals
5	5.0_dimensionality_reduction_PCA.ipynb	Dimensionality Reduction, PCA
6	6.0_kernel_methods.ipynb	Kernel Methods
7	7.0_mixture_model_&_probability.ipynb	Mixture Models, Probability Theory
8	8.0_information_theory_decision_tree.ipynb	Information Theory, Decision Trees
9	9.0_generative_model_basic.ipynb	Generative Models

🚀 Projects

Movie Review Sentiment Classifier

Location: projects/movie_review_sentiment_classifier-master/

A production-ready sentiment analysis project using fine-tuned transformer models.

Key Files:

• README.md - Project documentation
• setup.py - Package configuration
• src/api/main.py - FastAPI application
• src/ml/model.py - Model training
• src/ml/data.py - Data handling
• notebooks/movie_review_sentiment_classifier.ipynb - Main notebook

Features:

• Fine-tuned transformer models for sentiment classification
• REST API with FastAPI
• Comprehensive logging
• Data preprocessing pipeline
• Model training and evaluation

See the project README for detailed setup and usage instructions.

5. Running Projects

Each project has its own setup instructions. See the individual project README:

cd projects/movie_review_sentiment_classifier-master/
pip install -r requirements.txt
pip install -e .

🎯 Quick Links

• Exercises: exercises/foundation/
• Projects: projects/
• Sentiment Classifier Project: projects/movie_review_sentiment_classifier-master/
  • Project README
  • API Main File
  • Model Implementation

📁 Repository Structure

MachineLearningPortfolio/
├── README.md                          # This file
├── .gitignore                         # Git ignore patterns for entire portfolio
├── requirements.txt                   # Python dependencies
├── common/                            # Shared utilities (currently empty)
├── exercises/                         # Learning materials & exercises
│   └── foundation/                    # Foundational ML concepts
│       ├── 1.0_basic.ipynb           # Basic concepts
│       ├── 2.0_linear_regression_&_svm.ipynb
│       ├── 3.0_generalization_&_evaluation_cm.ipynb
│       ├── 4.0_neural_network_basic.ipynb
│       ├── 5.0_dimensionality_reduction_PCA.ipynb
│       ├── 6.0_kernel_methods.ipynb
│       ├── 7.0_mixture_model_&_probability.ipynb
│       ├── 8.0_information_theory_decision_tree.ipynb
│       └── 9.0_generative_model_basic.ipynb
└── projects/                          # Real-world ML projects
    └── movie_review_sentiment_classifier-master/
        ├── README.md                  # Project-specific documentation
        ├── .gitignore                 # Project-specific git patterns
        ├── setup.py                   # Package setup configuration
        ├── NOTE.MD                    # Deployment notes
        ├── requirements.txt           # Project dependencies
        ├── src/                       # Source code
        │   ├── api/                   # FastAPI application
        │   │   ├── main.py           # FastAPI app setup
        │   │   ├── logs/             # API logs
        │   │   └── routes/
        │   │       └── predict.py    # Prediction endpoints
        │   ├── ml/                    # Machine learning module
        │   │   ├── __init__.py
        │   │   ├── model.py          # Model training & inference
        │   │   ├── data.py           # Data loading & preprocessing
        │   │   └── utils.py          # Utility functions
        │   └── logging_utils/         # Logging configuration
        │       ├── __init__.py
        │       └── logger.py         # Logger setup
        ├── notebooks/                 # Jupyter notebooks
        │   ├── 01_exploration.ipynb
        │   ├── movie_review_sentiment_classifier.ipynb
        │   └── logs/                 # Notebook logs
        └── data/                      # Data storage
            ├── raw/                   # Raw datasets
            └── processed/             # Processed datasets

📝 Project Notes

• Detailed deployment and implementation notes for the sentiment classifier are available in projects/movie_review_sentiment_classifier-master/NOTE.MD
• Each project directory has its own .gitignore for project-specific patterns
• The root .gitignore covers common patterns for the entire portfolio