Repository contains my Jupyter Notebook files (ran either in VSCode using the Jupyter Notebook extension, either Notebook or Lab through Anaconda, or Google Colab) for a Multilayer Perceptron (MLP) capable of predicting wine scores and classifying quality, for EEL6812 - Advanced Topics in Neural Networks (Deep Learning with Python) course, PRJ01

This repository focuses on handwritten digit recognition using the MNIST dataset. It includes implementations of Logistic Regression, MLP, and LeNet-5 in PyTorch, organized into folders for reports, flowcharts, scripts, and notebooks, with detailed instructions for preprocessing and training.

Repository of all notebooks used in the ML-DL101 event for explaining basics of machine learning and deep learning.

This repository contains a collection of fundamental topics and techniques in machine learning. It aims to provide a comprehensive understanding of various aspects of machine learning through simplified notebooks. Each topic is covered in a separate notebook, allowing for easy exploration and learning.

Slides and notebooks for my tutorial at PyData London 2018