Pinned Repositories
Algorithms-python
All Algorithms implemented in Python
autoencoders
coding-interview-university
A complete computer science study plan to become a software engineer.
deep_generative_models
Docker-Tips
info8010-deep-learning
Lectures for INFO8010 - Deep Learning, ULiège
link_game
LSTM_Networks
This is the code for "LSTM Networks - The Math of Intelligence (Week 8)" By Siraj Raval on Youtube
rl-demos
tf_learning
The code is from a TensorFlow tutorial introduced by Aladdin Persson (https://www.youtube.com/playlist?list=PLhhyoLH6IjfxVOdVC1P1L5z5azs0XjMsb).
shengli-xu's Repositories
shengli-xu/Algorithms-python
All Algorithms implemented in Python
shengli-xu/autoencoders
shengli-xu/coding-interview-university
A complete computer science study plan to become a software engineer.
shengli-xu/deep_generative_models
shengli-xu/Docker-Tips
shengli-xu/info8010-deep-learning
Lectures for INFO8010 - Deep Learning, ULiège
shengli-xu/link_game
shengli-xu/LSTM_Networks
This is the code for "LSTM Networks - The Math of Intelligence (Week 8)" By Siraj Raval on Youtube
shengli-xu/my_config
shengli-xu/rl-demos
shengli-xu/tf_learning
The code is from a TensorFlow tutorial introduced by Aladdin Persson (https://www.youtube.com/playlist?list=PLhhyoLH6IjfxVOdVC1P1L5z5azs0XjMsb).
shengli-xu/machine-learning-notes
My continuously updated Machine Learning, Probabilistic Models and Deep Learning notes and demos (1000+ slides) 我不间断更新的机器学习，概率模型和深度学习的讲义(1000+页)和视频链接
shengli-xu/markdown-it-vue
The vue lib for markdown-it.
shengli-xu/pandas-cookbook
Recipes for using Python's pandas library
shengli-xu/PRML
PRML algorithms implemented in Python
shengli-xu/python-pcl
Python bindings to the pointcloud library (pcl)
shengli-xu/shengli-xu.github.io
Resume
shengli-xu/sklearn-ml
各种机器学习方法在sklearn中的使用-菜菜的机器学习sklearn课堂
shengli-xu/TrainYourOwnYOLO
Train a state-of-the-art yolov3 object detector from scratch!
shengli-xu/triangle_analysis
Find triangles in each picture and calculate the perimeter.
shengli-xu/tuning_playbook
A playbook for systematically maximizing the performance of deep learning models.