TensorFlow implementations of several deep learning models (e.g. variational autoencoder, RNN, ...)

App that detects severity of Diabetic Retinopathy using TensorflowLite model trained from scratch in Google Colab notebook.

Collection of notebooks I made on deep learning topics.

The notebook in the repo can be considered as a tutorial for building a CNN using pytorch.

Jupyter notebooks implementing Deep Learning algorithms in Keras and Tensorflow

Notes and Jupyter notebooks exploring deep learning and Tensorflow framework

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 Convolutional Neural Network (CNN) that classifies Dogs, Cats, and Pandas, for EEL6812 - Advanced Topics in Neural Networks (Deep Learning with Python) course, PRJ02

Several notebooks that cover various ML concepts such LR, CNN's, RNN's, & more!

This repository contains a Jupyter Notebook file equipped with code for identifying the position of digits in a Sudoku puzzle and solving it. The notebook implements algorithms for Sudoku puzzle solving, offering a practical tool for enthusiasts and learners alike to explore and understand Sudoku solving techniques. 2-2 METHODS FOR BOTH TASKS.

A collection of Jupyter notebooks containing various MNIST digit and fashion item classification implementations using fully-connected and convolutional neural networks (CNNs) built with TensorFlow and Keras. 2020.

CNN applied on Cifar-10 database.

This project implements deep learning models for classifying images. Using TensorFlow and Keras, it includes scripts and notebooks for training and testing neural networks on various datasets to achieve high accuracy in image categorization.