https://github.com/dn070017/neural-networks-basics
Neural Networks Basics using Tensorflow
https://github.com/dn070017/neural-networks-basics
neural-networks tensorflow
Last synced: about 2 months ago
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Neural Networks Basics using Tensorflow
- Host: GitHub
- URL: https://github.com/dn070017/neural-networks-basics
- Owner: dn070017
- License: mit
- Created: 2020-09-03T07:03:02.000Z (almost 6 years ago)
- Default Branch: master
- Last Pushed: 2021-01-14T12:29:34.000Z (over 5 years ago)
- Last Synced: 2025-03-03T08:14:19.253Z (over 1 year ago)
- Topics: neural-networks, tensorflow
- Language: Jupyter Notebook
- Homepage: https://www.notion.so/Neural-Network-Basics-6c71b218abc14bb89e2fa21f35066c54
- Size: 1.4 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Data Science Notes Figures
## Introduction
This repository contains the jupyter notebook, scripts, figures and interactive visualization for neural networks using Tensorflow. Please contact me if the content posted here is incorrect.
## View Interactive Visualization
To view the interactive visualization, please use the following command:
```bash
bokeh serve --show visualization/[file.py]
```
## Table of Contents
### [Tensors and Variables](notebooks/tensors_and_variables.ipynb)
### [Jacobian Matrix and Gradient](notebooks/jacobian_matrix_and_gradient.ipynb)
### [Activation Functions](notebooks/activation_functions.ipynb)
### [Objective Functions](notebooks/objective_functions.ipynb)
### [Gradient Descent](notebooks/gradient_descent.ipynb)
### [Optimizers](notebooks/optimizers.ipynb)
### [Tensorflow Data](notebooks/tensorflow_data.ipynb)
### [Multilayer Perceptron](notebooks/multilayer_perceptron.ipynb)