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DL

Simple_Neural_Network

build a simple network to make predictions of bike-sharing usage

Sentiment_Classification

build a network for sentiment analysis on the movie review data

Object_Recognition

  • Object_Recognition.ipynb: build a neural network classify images from the CIFAR-10 dataset
  • Digit_Recognition: build a neural network that recognizes handwritten numbers using the MNIST data set

Recurrent_Neural_Network

  • Intro_to_RNN: build a character-wise RNN trained on Anna Karenina
  • How-to-Generate-Music-Demo: uses Keras & Theano to generate jazz music

Skip_Gram_word2vec

train a network to learn representations for words that show up in similar contexts

Generate_TV_Scripts

generate a new TV script for a scene at Moe's Tavern

Transfer_Learning

take a pre-trained neural network (e.g AlexNet, VGG, GoogLeNet, ResNet) and adapting the neural network to a new, different data set

Translation_Chatbot

Reinforcement_Learning

  • Q-learning-cart.ipynb: use Q-learning to train an agent to play a game called Cart-Pole
  • Smartcab: implement a Q-Learning algorithm for the self-driving agent to guide the agent towards its destination within the allotted time

Generative_Adversarial_Network

  • Intro_to_GANs.ipynb: build a generative adversarial network (GAN) trained on the MNIST dataset
  • Autoencoders: build a simple autoencoder to compress the MNIST dataset
  • Deep_Convolutiona_GANs: implement the Deep Convolutional GAN model to generate full color images
  • Generate_Faces: use a generative adversarial network (GAN) to generate novel faces
  • How_to_generate_video

One_Shot_Learning

Stanford_CS20SI_tensorflow_for_deep_learning_research

contains code examples for the course CS 20SI: TensorFlow for Deep Learning Research

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