Machine Learning Fun Projects

Welcome to the Machine Learning Fun Projects! This repository contains four different projects that provide a very basic intro to the world of deep learning. From basic concepts like regression and classification to more LSTMs and Transformers. They are designed to be both educational and enjoyable for those new to machine learning and deep learning.

Table of Contents

1. Simple Linear Regression
2. Classification with MNIST
3. Text Generation with LSTM
4. Versatile Transformer Model

Simple Linear Regression

Description

Very basic regression task using linear regression. It helps you understand the fundamental concept of predicting a continuous output variable based on one or more input features.

Usage

python regression.py

Classification with CIFAR10

Description

Image classification with the CIFAR10 dataset. Training a neural network to classify handwritten digits.

Usage

python classification.py

Text Generation with LSTM

Description

Long Short-Term Memory (LSTM) networks by generating text. This project explores how LSTMs can be used to learn from sequences of data and generate coherent text.

Usage

python textgeneration.py

Transformer Model

Description

Transformers are the backbone of many state-of-the-art models in natural language processing and other fields. This project provides a versatile Transformer model that can be adapted for various tasks such as translation, summarization, and more.

Usage

python transformer.py