Machine-Learning 🎭

This repository is mainly for creative ideas in regards to machine learning and algorithms.

Highlighted Projects

• Loading, tokenising and training a language model using Tiny Shakespeare (Project Two)
• Predicting student scores and house prices using Linear Regression Modelling (Project Three + Project Four)
• Gradio application for summarising input (Project Six)

This repository contains many projects on machine learning

• Project One, learn about pipelines, tokenisation, prompt batching and temperature
• Project Two, learn about loading datasets, tokenising datasets, training a model and fine-tuning
• Project Three, learn about linear and logistic regression models
• Project Four, learn about decision trees and random forests
• Project Five, learn about Gradio and other types of model configurations (e.g. summarise)
• Project Six, more custom Gradio apps and advanced models

## 📂 Project Structure

project_one/
├── notes.txt
├── requirements.txt
├── pipeline.py
├── expanded_pipeline.py
├── tokenization_demo.py
├── temperature_demo.py
└── prompt_batching.py

project_two/
├── notes.txt
├── requirements.txt
├── load_shakespeare.py
├── tokenize_shakespeare.py
├── training_shakespeare.py
└── training_shakespeare_theory.py

project_three/
├── notes.txt
├── requirements.txt
├── basic_linear_regression.py
├── basic_logistic_regression.py
├── graph_linear_regression.py
└── graph_logistic_regression.py

project_four/
├── notes.txt
├── requirements.txt
├── basic_decision_tree.py
├── basic_random_forest.py
├── Housing.csv
├── house_price_prediction.py

project_five/
├── notes.txt
├── requirements.txt
├── summariser.py
├── summariser_gradio.py
├── summariser_gradio_upgrade.py

project_six/
├── notes.txt
├── requirements.txt
├── gradio_app.py

⚙️ Setup

1. Clone the repo

git clone https://github.com/darkcom109/Machine-Learning.git
cd Machine-Learning

2. Set up a virtual environment in a project

python -m venv venv

3. Install dependencies in a project

pip install -r requirements.txt