Notebooks 📚

This repository contains a list of jupyter notebooks, mostly results of my experiments, references from books and other project based explorations

List of Contents

1) California Housing Price Prediction 🏠🌴

Predicting housing prices in a given area in california, based on the book Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow. Modified to use seaborn 🌊 instead of matplotlib 📊.

2) MNIST Dataset 3️⃣

Classification of digits from the open source MNIST dataset, also based on the book Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow. Modified to use seaborn 🌊 instead of matplotlib 📊.

3) Regression Model 📈

A basic model to demonstrate Linear Regression using PyTorch

4) Circle Classification 🔵

A basic model to classify circles using non-linear activation functions using PyTorch, based on the sklearn toy dataset