https://github.com/lovesaroha/learning-neural-networks

Various concepts of neural networks applied in python (numpy) to help people get started with AI.
https://github.com/lovesaroha/learning-neural-networks

batch-normalization dropout gradient-descent logistic-regression neural-network numpy python regularization

Last synced: 7 days ago
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Various concepts of neural networks applied in python (numpy) to help people get started with AI.

• Host: GitHub
• URL: https://github.com/lovesaroha/learning-neural-networks
• Owner: lovesaroha
• License: gpl-3.0
• Created: 2021-09-15T07:31:41.000Z (about 3 years ago)
• Default Branch: main
• Last Pushed: 2021-09-17T07:03:03.000Z (about 3 years ago)
• Last Synced: 2024-01-26T05:14:17.631Z (10 months ago)
• Topics: batch-normalization, dropout, gradient-descent, logistic-regression, neural-network, numpy, python, regularization
• Language: Python
• Homepage:
• Size: 17.6 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Learning-Neural-Networks (Python)

Various concepts of neural networks applied in python (numpy) to help people get started with AI. 

## Examples

- Logistic Regression.

- Logistic Regression With Regularization.

- Simple Neural Network.

- Neural Network With Mini Batches.

- Neural Network With Regularization.

- Neural Network With Gradient Check.

- Neural Network With Dropout.

- Neural Network With Batch Norm.

- Neural Network With Optimization Algorithms (Momentum , RMSProp , Adam).