https://github.com/valeman/deep-learning-nanodegree--udacity-
All codes related to Udacity's Deep Learning Nano Degree program
https://github.com/valeman/deep-learning-nanodegree--udacity-
Last synced: 8 months ago
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All codes related to Udacity's Deep Learning Nano Degree program
- Host: GitHub
- URL: https://github.com/valeman/deep-learning-nanodegree--udacity-
- Owner: valeman
- Created: 2017-03-15T16:36:53.000Z (about 9 years ago)
- Default Branch: master
- Last Pushed: 2017-03-03T00:51:32.000Z (over 9 years ago)
- Last Synced: 2025-03-16T07:11:24.965Z (about 1 year ago)
- Language: Jupyter Notebook
- Size: 33.1 MB
- Stars: 1
- Watchers: 1
- Forks: 3
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Deep Learning - NanoDegree (Udacity)
This repository contains all the codes for assignments and projects that are a part of the Deep Learning NanoDegree program at Udacity.
__The following is a developing list of code that can be found in this repository:__
1. Build Neural Net from Scratch -- In this project I built a neural network from scratch using Numpy only. I implemented the backpropagation and forward propagation methods from scratch and then used the network to predict bike sharing.
2. Sentiment Network -- Here I take our neural network built in project 1 and used it to classify sentiments in texts. Here I implemented the word to vector and bag of words functions from scratch.
3. Sentiment Analysis using TFlearn - Here I used TFlearn to implement a sentiment analysis algorithm using neural networks.
4. MNIST Using TFlearn - In this assigment, I used TFlearn to successfully classify the MNIST handwritten digits using a deep neural network
5. Sentiment Analysis IMDB Recurrent Neural Net - Here I used recurrent neural networks to train a model to classify IMDB reviews as positive or negative
6. Intro to TensorFlow - In this, I have used TensorFlow to normalize, train and predict on the non-MNIST data.
For any suggestions, please write to soutikc@uw.edu