https://github.com/snehilsanyal/tensorflow-2-for-deep-learning-specialization-coursera

Repository for the course TensorFlow 2 for Deep Learning Specialization (Coursera) offerred by Imperial College of London
https://github.com/snehilsanyal/tensorflow-2-for-deep-learning-specialization-coursera

coursera deep-learning tensorflow tensorflow-tutorials

Last synced: 12 days ago
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Repository for the course TensorFlow 2 for Deep Learning Specialization (Coursera) offerred by Imperial College of London

• Host: GitHub
• URL: https://github.com/snehilsanyal/tensorflow-2-for-deep-learning-specialization-coursera
• Owner: snehilsanyal
• Created: 2022-05-28T10:50:44.000Z (over 2 years ago)
• Default Branch: main
• Last Pushed: 2022-06-01T13:01:32.000Z (over 2 years ago)
• Last Synced: 2024-10-10T08:40:53.987Z (about 1 month ago)
• Topics: coursera, deep-learning, tensorflow, tensorflow-tutorials
• Language: Jupyter Notebook
• Homepage: https://www.coursera.org/specializations/tensorflow2-deeplearning
• Size: 1.47 MB
• Stars: 1
• Watchers: 1
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# TensorFlow 2 for Deep Learning Specialization Coursera

The [TensorFlow 2 for Deep Learning Specialization](https://www.coursera.org/specializations/tensorflow2-deeplearning) is offered by Imperial College of London. The instructor of this specialization is [Dr. Kevin Webster](https://www.imperial.ac.uk/people/kevin.webster). This specialization consists of three courses each 5 week long. The first 4 weeks build on concepts with some assignments and practice, whereas the final week is for Capstone Project.

## Courses

**1. Getting Started with TensorFlow 2**

**2. Customising your Models with TensorFlow 2**

**3. Probabilistic Deep Learning using TensorFlow 2**

- This repository contains 3 folders each for the 3 courses, each course folder consists of 5 folders for each week from **Week 1** to **Week 5**.

- Each week's folder contains a Readme file (do read it) which provides the organization of the topics in that particular course and information on how to run the code samples.

- Each week's folder contains code samples, which I compiled as I was going through the introductory lectures (by Dr. Kevin Webster) and exercise lectures (by TAs). These code samples are well commented, and are provided to aid the videos of the corresponding week. 

- Assignment or tutorial are provided in both script and .ipynb notebook format. Making the code public is just to make sure that the learners are not facing any issue in understanding the concepts, if you directly use the assignment notebooks without going through it you are killing your learning curve. 

- This repository wont provide quiz responses, but if you would like to discuss quiz responses we can open up Discussions.

- Please feel free to open up any issue in the code.