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Codes for "Abnormal Event Detection in Videos using Spatiotemporal Autoencoder".
The classical paper list with code about generative adversarial nets
Dynamic anomaly detection in crowded scene videos using sparse autoencoders
Movie review anomaly detector based on the auto_encoder configured GRU+Attention model
List of tools & datasets for anomaly detection on time-series data.
Computer Science Bachelor thesis exploring the effectiveness of using recurrent neural networks for anomaly detection in the Los Alamos cyber-security data set.
An open-source framework for real-time anomaly detection using Python, ElasticSearch and Kibana
A tensorflow implementation of "Deep Convolutional Generative Adversarial Networks"
Continuous control with deep reinforcement learning - Deep Deterministic Policy Gradient (DDPG) algorithm implemented in OpenAI Gym environments
Using Keras and Deep Deterministic Policy Gradient to play TORCS
Machine Learning tutorials with TensorFlow 2 and Keras in Python (Jupyter notebooks included) - (LSTMs, Hyperameter tuning, Data preprocessing, Bias-variance tradeoff, Anomaly Detection, Autoencoders, Time Series Forecasting, Object Detection, Sentiment Analysis, Intent Recognition with BERT)
Minimal Deep Q Learning (DQN & DDQN) implementations in Keras
Implementation of 'A Distributional Perspective on Reinforcement Learning' and 'Distributional Reinforcement Learning with Quantile Regression' based on OpenAi DQN baselines.
Extended Mean Field Restricted Boltzmann Machine
Frame level anomaly detection and localization in videos using auto-encoders
Collection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow.
Keras implementations of Generative Adversarial Networks.
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Example code for neural-network-based anomaly detection of time-series data (uses LSTM)
LSTM built using Keras Python package to predict time series steps and sequences. Includes sin wave and stock market data
A try to autoencode an LSTM to do anomaly detection
News, full-text, and article metadata extraction in Python 3. Advanced docs:
random search, hill climbing, policy gradient
A simulation for an experiment of my paper work. Focus on encoding & decoding feature vectors of network packets with RNN-RBM & GBRBM
Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.
Gathers machine learning and deep learning models for Stock forecasting including trading bots and simulations
This project provides a stock market environment using OpenGym with Deep Q-learning and Policy Gradient.
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A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.