https://github.com/ramapinnimty/hands-on-tensorflow

Systematic and complete notes (or guide) on getting started right away with Tensorflow. Inspired from "Complete Guide to Tensorflow for Deep Learning with Python" on Udemy.
https://github.com/ramapinnimty/hands-on-tensorflow

beginners estimator-api python3 tensorflow tensorflow-tutorials

Last synced: 3 months ago
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Systematic and complete notes (or guide) on getting started right away with Tensorflow. Inspired from "Complete Guide to Tensorflow for Deep Learning with Python" on Udemy.

• Host: GitHub
• URL: https://github.com/ramapinnimty/hands-on-tensorflow
• Owner: ramapinnimty
• License: mit
• Created: 2018-12-22T11:06:08.000Z (over 7 years ago)
• Default Branch: master
• Last Pushed: 2018-12-22T11:35:41.000Z (over 7 years ago)
• Last Synced: 2025-02-21T15:53:15.434Z (over 1 year ago)
• Topics: beginners, estimator-api, python3, tensorflow, tensorflow-tutorials
• Language: Jupyter Notebook
• Size: 1010 KB
• Stars: 0
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# Hands-on-Tensorflow

![Tensorflow Image](https://www.tertiarycourses.com.sg/media/catalog/product/cache/1/image/650x/040ec09b1e35df139433887a97daa66f/d/e/deep-learning-machine-learning-tensorflow.jpg)

Systematic and complete notes (or guide) on getting started right away with Tensorflow. Inspired from "Complete Guide to Tensorflow for Deep Learning with Python" course offered via Udemy.

Requirements:

------------

1. Some knowledge of programming (preferably Python).

2. Some basic knowledge of math (mean, standard deviation, etc..).

Contents:-

--------

1. Tensorflow Basics.

2. Basic Neural Network for Regression using NumPy, Tensorflow.

3. Use TensorFlow's Estimator API for Regression.

  *  3.1 Regression exercise.

4. Use TensorFlow's Estimator API for Classification.

  *  4.1 Classification exercise.

5. Use TensorFlow for Image Classification with Convolutional Neural Networks (CNN's).

6. Use TensorFlow for Time Series Analysis with Recurrent Neural Networks (RNN's).

7. Use TensorFlow for solving Unsupervised Learning Problems with AutoEncoders.

8. Create Generative Adversarial Networks (GAN's) with TensorFlow.