Python codes in Machine Learning, NLP, Deep Learning and Reinforcement Learning with Keras and Theano

Spatial pyramid pooling layers for keras

Keras implementation of Phased LSTM [https://arxiv.org/abs/1610.09513]

Implementations for a family of attention mechanisms, suitable for all kinds of natural language processing tasks and compatible with TensorFlow 2.0 and Keras.

Batch Renormalization algorithm implementation in Keras

Neural Tensor Network Implementation as a keras layer

Keras implementation of ontology aware token embeddings

Keras model convolutional filter pruning package

Utilities for Keras - Deep Learning library

Restricted Boltzmann Machines as Keras Layer

CRF(Conditional Random Field) Layer for TensorFlow 1.X with many powerful functions

A collection of layers, ops, utilities and more for TensorFlow 2.0 high-level API Keras

A Keras layer that acts as multiplexer for Dense layers (Tensorflow backend only)

Utility for extracting layer weights and biases from Keras models

A detailed Research project on Character-Segmentation using Neural Networks!

Keras and tensorflow transfer learning, starting from the pre-trained inception_resnetV2 model

language model for basic jack and jill poem using RNN

Códigos Python com diferentes aplicações como técnicas de machine learning e deep learning, fundamentos de estatística, problemas de regressão de classificação. Os vídeos com as explicações teóricas estão disponíveis no meu canal do YouTube

A Keras implementation of the paper "Robust Graph Convolutional Networks Against Adversarial Attacks"

Deep Neural Networks with Keras and Tensorflow.Deep learning is one of the leading tools in data analysis these days and one of the most common frameworks for deep learning is Keras.

ConvNet (CNN) implementation to classify x-ray medical images

This repository contains starting files for the Behavioral Cloning Project. In this project, you will use what you've learned about deep neural networks and convolutional neural networks to clone driving behavior. You will train, validate and test a model using Keras. The model will output a steering angle to an autonomous vehicle. We have provided a simulator where you can steer a car around a track for data collection. You'll use image data and steering angles to train a neural network and then use this model to drive the car autonomously around the track. We also want you to create a detailed writeup of the project. Check out the writeup template for this project and use it as a starting point for creating your own writeup. The writeup can be either a markdown file or a pdf document. To meet specifications, the project will require submitting five files: model.py (script used to create and train the model) drive.py (script to drive the car - feel free to modify this file) model.h5 (a trained Keras model) a report writeup file (either markdown or pdf) video.mp4 (a video recording of your vehicle driving autonomously around the track for at least one full lap) This README file describes how to output the video in the "Details About Files In This Directory" section.

Beginning with NLP

Image classification using Keras and implement forward pass using Python(only numpy) and C++ for FPGA

Keras, Tensorflow eager execution layers for exponential smoothing

Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning - Coursera course practice files.

Seq2Seq model that restores punctuation on English input text.

Predict Sentiment From Movie Review Using Deep Learning