This repository is dedicated to providing a comprehensive yet beginner-friendly guide to various deep learning optimizers. You'll find detailed explanations and implementations of popular optimizers like SGD, Adam, and RMSProp, along with a visualizer to help you understand their behaviors. Whether you're new to deep learning or looking to solidify your understanding, this resource is designed to make the learning process easier and more interactive.
- Comprehensive Optimizer Implementations: Includes class-based and functional implementations of popular deep learning optimizers such as SGD, Adam, RMSProp, and more.
- Interactive Visualizer:
app.py
provides a visual tool to observe and compare the behavior and performance of different optimizers in real-time. - Beginner-Friendly Guide: Detailed explanations and step-by-step tutorials make complex concepts accessible for beginners in deep learning.
- Practical Examples: Real-world examples and use cases to demonstrate the practical application of each optimizer in various deep learning scenarios.
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Clone the repository
git clone https://github.com/NotShrirang/optim.git cd optim
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Install the required dependencies
pip install -r requirements.txt
To run streamlit app locally.
streamlit run app.py
MIT © Shrirang Mahajan
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