https://github.com/m-bkh-t/deep-learning-course

In this learning path, you will be able to learn the basic concepts of Deep Leaning and TensorFlow
https://github.com/m-bkh-t/deep-learning-course

jupyter-notebook python3 tensorflow

Last synced: about 1 month ago
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In this learning path, you will be able to learn the basic concepts of Deep Leaning and TensorFlow

• Host: GitHub
• URL: https://github.com/m-bkh-t/deep-learning-course
• Owner: M-BKH-T
• Created: 2024-09-10T14:43:35.000Z (2 months ago)
• Default Branch: main
• Last Pushed: 2024-09-28T15:37:19.000Z (about 2 months ago)
• Last Synced: 2024-10-15T17:04:05.965Z (about 1 month ago)
• Topics: jupyter-notebook, python3, tensorflow
• Language: Jupyter Notebook
• Homepage:
• Size: 421 KB
• Stars: 4
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
- # Hi there,I'm ___M-BKH-T___ 👋

### You arrived on time. We have a deep learning course here. Join us if you want to learn

# About this Learning Path

In this `learning path`, you will be able to learn the basic concepts of `Deep Leaning` and `TensorFlow`. Then, you will get hands-on experience in solving problems using Deep Learning. Starting with a simple “Hello Word” example, throughout the course you will be able to see how TensorFlow can be used in curve fitting, regression, classification and minimization of error functions. This concept is then explored in the Deep Learning world. You will learn how to apply TensorFlow for backpropagation to tune the weights and biases while the Neural Networks are being trained.

# Prerequisites for this course

The prerequisite for this course is that you have already passed the machine learning course or are familiar with its concepts.

# __Skills you'll gain__

 

 `Artificial Neural Network` `Backpropagation`

`Python Programming` 

 `Deep Learning` 

 `Neural Network Architecture` `TensorFlow`