BERT QnA API to answer prompts based on Context. (Using CDN)

Build a Convolutional Neural Network to classify if an image depicts a Vehicle.

LinguaNet is a language identification model built on DNNs using Python and TensorFlow. It utilizes character n-grams for accurate language classification. With an 89.2% accuracy, LinguaNet effectively identifies and differentiates languages. The repository includes model details, visualization of learned features, and implementation code.

Sota Tek Machine Learning blog

Generate new Simpson's TV scripts using neural network

Udacity self driving car nanodegree

A text generating neural network.

Udacity Deep Learning Foundation Project3 Generate TV Scripts

Recognizing traffic signs with deep convolutional neural networks

How to use Deep Neural Networks and Convolutional Neural Networks to classify Traffic Signs

Udacity Deep Learning Nano Degree : Project-3 : TV Script Generation using RNN

A CNN to identify dog breeds (P2 - DLND)

Udacity Machine Learning Engineer Nanodegree Convolutional Neural Networks (CNN) Project: Dog Breed Classifier

Tool to predict places where most buying and selling of real estate would happen based on historic data.

building a classifier to recognize traffic signs using deep neural networks and convolutional neural networks.

Case studies using TensorFlow 2.0

Official Website of Kaggle Datasets