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Important Resources and Workspace Notebooks as mentioned in the Udacity Deep Learning Nanodegree. WELCOME to Udacity DLND Workspace

License: Apache License 2.0

Jupyter Notebook 51.54% HTML 48.33% Python 0.14% Shell 0.01%

udacity-deep-learning-nanodegree-workspace's Introduction

Udacity-Deep-Learning-Nanodegree-Workspace

This repo contains all the important resources and workspace notebooks as mentioned in the Udacity Deep Learning Nanodegree.

You need to have a proper GPU service for launching and running the Jupyter Notebooks.If you don't have a GPU service, you can still go through via Google Colabs or AWS Services:Amazon SageMaker.

The steps needed to go through this resource:-

1. Clone the repository git clone https://github.com/blackeye735/Udacity-Deep-Learning-Nanodegree-Workspace
2. Install Ananoconda or Install Pip utility
3. Run pip install jupyter notebook(for pip) or Run conda jupyter notebook
4. Go through the README.md file to understand the project
5. Run the Notebook (.ipynb files) to get the appropriate results.

Contents of this Resource:-

1. Intro to Deep Learning

2. Neural Networks

3. Convolutional Neural Networks

4. Recurrent Neural Networks

5. Generative Adversarial Networks

6. Deploying a Trained model via AWS SageMaker

7. Additional - KERAS & TENSORFLOW

I had been lucky enough to get a month free trial for Udacity Deep Learning Nanodegree.Starting from 30th of April, I completed each and every workspace, and submitted each and every project on 26th of May.

The reward that I got is:-

You can have a look at Udacity_DLND_blackeye735 or view it directly from UDACITY website.

Thank you Udacity for this wonderful experience.

MADE WITH LOVE BY ARGHO CHAKRABORTY

The codes are not for copying.It ensures copyright issues on the repository.Plagarism is not at all entertained.For further details, check our CODE OF CONDUCT.

License:- The repo has been licensed by APACHE LICENSE 2.0.

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