MingchaoZhu/DeepLearning
Python for《Deep Learning》，该书为《深度学习》(花书) 数学推导、原理剖析与源码级别代码实现
This project offers detailed mathematical derivations and foundational Python code implementations for concepts from the "Deep Learning" textbook by Goodfellow, Bengio, and Courville. It takes complex theoretical ideas from the book and provides plain-language explanations, mathematical proofs, and corresponding Python code (primarily using NumPy). Students and researchers in fields like AI, machine learning, and data science can use this resource to deepen their understanding of deep learning algorithms.
7,579 stars. No commits in the last 6 months.
Use this if you are a university student or researcher studying deep learning and need to understand the underlying mathematical principles and implement algorithms from scratch without relying on high-level frameworks.
Not ideal if you are a practitioner looking for ready-to-use deep learning models or seeking to implement solutions quickly using established deep learning frameworks like TensorFlow or PyTorch.
Stars
7,579
Forks
1,442
Language
Python
License
MIT
Category
Last pushed
Jun 23, 2020
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/MingchaoZhu/DeepLearning"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Related frameworks
PaddlePaddle/Paddle
PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice...
fastai/fastai
The fastai deep learning library
openvinotoolkit/openvino_notebooks
📚 Jupyter notebook tutorials for OpenVINO™
PaddlePaddle/docs
Documentations for PaddlePaddle
msuzen/bristol
Parallel random matrix tools and complexity for deep learning