Machine Learning

Beginner ML projects for learning by running, inspecting, modifying, and rebuilding.

Setup

python3 -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt

Run the Titanic survival classifier:

python 01_titanic_survival/train.py

Run the house price regression model:

python 02_house_price_regression/train.py

Run the spam detector:

python 03_spam_detector/train.py

Run the tiny neural network from scratch:

python 04_tiny_neural_network/train.py

Run the PyTorch neural network:

python 05_pytorch_neural_network/train.py

Run NumPy linear regression from scratch:

python 06_linear_regression_from_scratch/train.py

Run NumPy logistic regression from scratch:

python 07_logistic_regression_from_scratch/train.py

Run the MNIST digit classifier:

python 08_mnist_digit_classification/train.py

Open the EDA notebook:

09_data_processing_and_eda/eda_titanic.ipynb

Run the CIFAR-10 CNN:

python 10_cifar10_cnn/train.py --fake-data --epochs 1 --max-train-batches 5 --max-test-batches 2

Run the embeddings text classifier:

python 11_embeddings_text_classifier/train.py

Run the tiny transformer language model:

python 12_tiny_transformer_language_model/train.py --max-steps 20 --eval-interval 10