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Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.
此项目是机器学习(Machine Learning)、深度学习(Deep Learning)、NLP面试中常考到的知识点和代码实现，也是作为一个算法工程师必会的理论基础知识。
Gathers machine learning and deep learning models for Stock forecasting including trading bots and simulations
Python implementation of algorithms from Russell And Norvig's "Artificial Intelligence - A Modern Approach"
MIMIC Code Repository: Code shared by the research community for the MIMIC family of databases
Open-source implementation of Google Vizier for hyper parameters tuning
Experiments with Deep Learning
Python code for part 2 of the book Causal Inference: What If, by Miguel Hernán and James Robins
Code and slides of my YouTube series called "Audio Signal Proessing for Machine Learning"
Notes for the Reinforcement Learning course by David Silver along with implementation of various algorithms.
LUKE -- Language Understanding with Knowledge-based Embeddings
A simple probabilistic programming language.
Contains high quality implementations of Deep Reinforcement Learning algorithms written in PyTorch
PyTorch implementation of Anomaly Transformer: Time Series Anomaly Detection with Association Discrepancy
This repository is the code for Predictive Uncertainty Estimation using Deep Ensemble
Implementation of a model that predicts the SoH of batteries using the NASA Battery Dataset
Pytorch implementation of "Exploring Interpretable LSTM Neural Networks over Multi-Variable Data" https://arxiv.org/pdf/1905.12034.pdf
Pipeline to identify remaining useful life of Li-ion batteries using SVR to forecast end of life.
My blog.
Dual Staged Attention Model for Time Series prediction
KurochkinAlexey / Hierarchical-Attention-Based-Recurrent-Highway-Networks-for-Time-Series-Prediction
Pytorch implementation of Hierarchical Attention-Based Recurrent Highway Networks for Time Series Prediction https://arxiv.org/abs/1806.00685
Pytorch implementation of Dual-Stage Attention-Based Recurrent Neural Network for Time Series Prediction https://arxiv.org/pdf/1704.02971.pdf
A learning curve benchmark on OpenML data
A Dual-Stage Attention-Based Recurrent Neural Network for Time Series Prediction