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README
AI for Power Electronics
A comprehensive learning path for applying AI in Power Electronics Design.
1. Foundational
1.1 Python Basics
Basic Language Formats
1.2 Manage Environment and Dependencies
Package management with pip, conda, venv
1.3 Pythonic Programming
Python in 3 Days
30 Days of Python
2. Basic
2.1 Python Modules
NumPy
:
Numpy Tutorials
Pandas
:
Pandas Tutorial
Scikit-learn
:
Sklearn Tutorial
PyTorch
:
PyTorch Tutorials
2.2 Simulation Automation
PLECS
:
XMLRPC Controller Design
Simulink
:
Sim Command Guide
ANSYS
:
PyAnsys Documentation
LTspice
:
PyLTSpice Package
3. Intermediate
3.1 Meta-Heuristic Algorithms
Metaheuristics Library
PyMetaheuristic
3.2 Machine Learning
ML with Python
ML Tutorials
Ensemble Methods
3.3 Deep Learning
PyTorch Deep Learning
CS5242 Course
4. Advanced
4.1 Physics-informed Machine Learning
NVIDIA Modulus
Physics-Aware Neural Networks (PANN)
4.2 Generative AI for Power Electronics
PE-GPT: Power Electronics GPT
OpenAI Cookbook
4.3 Graph Neural Networks
Benchmarking GNNs
GNNs Recipe
4.4 Reinforcement Learning
RL Fundamentals
RL: An Introduction
4.5 Edge Deployment
Awesome Edge Machine Learning
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