chennanli's Stars
bukosabino/ta
Technical Analysis Library using Pandas and Numpy
musikalkemist/generating-sound-with-neural-networks
Code and slides for the "Generating Sound with Neural Network" series on The Sound of AI Youtube channel.
zhongqiangwu960812/AIGame
A recoding of a expreience about playing AI Game
LukeTonin/keras-seq-2-seq-signal-prediction
An implementation of a sequence to sequence neural network using an encoder-decoder
sdv-dev/DeepEcho
Synthetic Data Generation for mixed-type, multivariate time series.
CyC2018/CS-Notes
:books: 技术面试必备基础知识、Leetcode、计算机操作系统、计算机网络、系统设计
kamyu104/LeetCode-Solutions
🏋️ Python / Modern C++ Solutions of All 3292 LeetCode Problems (Weekly Update)
budaLi/leetcode-python-
一些实用的脚本工具及之前的leetcode算法题
unpingco/Python-for-Probability-Statistics-and-Machine-Learning-2E
Second edition of Springer Book Python for Probability, Statistics, and Machine Learning
unpingco/Python-for-Signal-Processing
Notebooks for "Python for Signal Processing" book
rlabbe/Kalman-and-Bayesian-Filters-in-Python
Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.
rlabbe/filterpy
Python Kalman filtering and optimal estimation library. Implements Kalman filter, particle filter, Extended Kalman filter, Unscented Kalman filter, g-h (alpha-beta), least squares, H Infinity, smoothers, and more. Has companion book 'Kalman and Bayesian Filters in Python'.
jianzhangcs/ISTA-Net
ISTA-Net: Interpretable Optimization-Inspired Deep Network for Image Compressive Sensing, CVPR2018 (Tensorflow Code)
JudasDie/deeplearning.ai
Some work of Andrew Ng's course on Coursera
enggen/Deep-Learning-Coursera
Deep Learning Specialization by Andrew Ng, deeplearning.ai.
Kulbear/deep-learning-coursera
Deep Learning Specialization by Andrew Ng on Coursera.
lexfridman/mit-deep-learning
Tutorials, assignments, and competitions for MIT Deep Learning related courses.
APMonitor/arduino
Process Control Temperature Lab
datasailors/probability
Probabilistic reasoning and statistical analysis in TensorFlow
susanli2016/Machine-Learning-with-Python
Python code for common Machine Learning Algorithms
CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
WillKoehrsen/Data-Analysis
Data Science Using Python
tensorflow/probability
Probabilistic reasoning and statistical analysis in TensorFlow
borisbanushev/stockpredictionai
In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.
emedd33/basic_reinforcement_learning
An introduction series to Reinforcement Learning (RL) with comprehensive step-by-step tutorials.
chainer/chainer-chemistry
Chainer Chemistry: A Library for Deep Learning in Biology and Chemistry