Machine Learning Projects

Portfolio folder with four standalone ML projects. Each project has its own README, dependencies, and (where applicable) git remote.

Project	Focus	Stack	Status
deep-learning-mnist	Handwritten digit CNN + Gradio UI (~99.33%)	PyTorch, Gradio	Showcase
stock-price-forecast-lstm	AAPL next-day LSTM forecast + Streamlit app	TensorFlow, Streamlit	Showcase (live demo)
Image-recognition/MNIST-MLP-CNN	MLP vs CNN comparison	TensorFlow/Keras	Comparison study
spam-classifier	SMS spam/ham with TF-IDF + logistic regression	scikit-learn	Classic NLP pipeline

How the two MNIST projects differ

deep-learning-mnist — production-style PyTorch CNN, training plots, interactive drawing UI.
MNIST-MLP-CNN — educational MLP baseline vs CNN comparison.

Open any project folder, create a venv, and follow that project’s README:

cd <project>
python -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt

This folder is published as a single monorepo:

Former individual repos (DEEP-LEARNING-MNIST, AAPL-LSTM-forecaster, MNIST-MLP-CNN) were consolidated here.

Name		Name	Last commit message	Last commit date
.streamlit		.streamlit
Image-recognition/MNIST-MLP-CNN		Image-recognition/MNIST-MLP-CNN
deep-learning-mnist		deep-learning-mnist
spam-classifier		spam-classifier
stock-price-forecast-lstm		stock-price-forecast-lstm
.gitignore		.gitignore
README.md		README.md