In this project, autonomous driving of a car around a cicular track is achieved using Deep Learning. Car driving skill and nature of human(s) is recorded and a network is trained to clone this behavior. The car then uses predictions fron the trained network to drive autonomously.

A Logistic Regression model which predicts and differentiates the diabetic patients from the given Pima Indians Diabetes Database dataset. Hyper parameter tuning is implemented using Tensorflow board visualizations.

Create a backend API to handle book information requests, and summary generation.

This works is an analysis of the feature space and comparison of the discriminative capability of features obtained from Autoencoders .In Deep learning literature these problems statements are called representation learning and through this work MNIST feature space and it's intricacies are visualized .

KAG CTF EU 3 2017-2018 word embeddings

This project was submitted as a requirement for this course. The course was administered in Spring 2018 in Tel-Aviv University - School of Mathematical Sciences

Domain: Computer Vision | Deep Learning

This is the code for "predict MNIST datasets using pure Tensorflow and Keras, a shallow learning model" By M.Junaid Fiaz

Predict whether a DonorsChoose.org project proposal submitted by a teacher will be approved.

This project demonstrates the use of various pre-trained models for transfer learning in NLP using TensorFlow Hub.

Homework for the advanced neural networks course

A Pytorch Project with flask API to predict handwritten digits using MNIST Dataset.

An LSTM model to label articles into 5 categories.

A model to classify images of waste products as Organic or Recyclable. Applied Image Augmentation to images and used basic CNN to classify images using Keras. Analysed the performance using Tensorboard. Detected over fitting using metric curves (accuracy) and addressed it using Dropout Regularization.

Neural Networks using Keras (with Image recognition case study)

Using Machine Learning and Deep Learning to predict the category of outdoor equipment

Dog breed classification with Tensorflow, Keras and Tranfer Learning.

My submissions for the mini project which was a part of my deep learning internship with Technocolabs

Solving the Atari Breakout environment using Stable Baselines