7290 Open source projects that are alternatives of or similar to Lstm_anomaly_thesis

List of papers, code and experiments using deep learning for time series forecasting

Jupyter Notebook tutorials on solving real-world problems with Machine Learning & Deep Learning using PyTorch. Topics: Face detection with Detectron 2, Time Series anomaly detection with LSTM Autoencoders, Object Detection with YOLO v5, Build your first Neural Network, Time Series forecasting for Coronavirus daily cases, Sentiment Analysis with BERT.

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PyTorch tutorial for learners

Anomaly detection implemented in Keras

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Example projects I completed to understand Deep Learning techniques with Tensorflow. Please note that I do no longer maintain this repository.

Deep learning codes and projects using Python

🥕 Evolutionary Neural Networks in JavaScript

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A collection of anomaly detection methods (iid/point-based, graph and time series) including active learning for anomaly detection/discovery, bayesian rule-mining, description for diversity/explanation/interpretability. Analysis of incorporating label feedback with ensemble and tree-based detectors. Includes adversarial attacks with Graph Convolutional Network.

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Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models

A Keras library for multi-step time-series forecasting.

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This project seeks to utilize Deep Learning models, Long-Short Term Memory (LSTM) Neural Network algorithm, to predict stock prices.

How to build RNNs and LSTMs from scratch with NumPy.

Tensorflow implementation of paper: Learning to Diagnose with LSTM Recurrent Neural Networks.

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)

Stock Price Prediction using Machine Learning Techniques

Awesome Artificial Intelligence, Machine Learning and Deep Learning as we learn it. Study notes and a curated list of awesome resources of such topics.

This is just a collection of projects that made during my DEEPLEARNING NANODEGREE by UDACITY

Tutorials on getting started with PyTorch and TorchText for sentiment analysis.

Using LSTM network for time series forecasting

Keras tutorial for beginners (using TF backend)

pytorch-kaldi is a project for developing state-of-the-art DNN/RNN hybrid speech recognition systems. The DNN part is managed by pytorch, while feature extraction, label computation, and decoding are performed with the kaldi toolkit.

Application of machine learning to the Coinbase (GDAX) orderbook

Neural machine translator for English2German translation.

Adventure into using multi attention recurrent neural networks for time-series (city traffic) for the 2017-11-18 McKinsey IronMan (24h non-stop) prediction challenge

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Implementation of "Generating Sequences With Recurrent Neural Networks" https://arxiv.org/abs/1308.0850

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A repository to keep track of all the code that I end up writing for my blog posts.

An End-to-end Outlier Detection System

Tutorial Sessions for SciPy Con 2019

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My journey to learn and grow in the domain of Machine Learning and Artificial Intelligence by performing the #100DaysofMLCode Challenge.

Variational Autoencoder for Dimensionality Reduction of Time-Series

Anomaly detection tutorial on univariate time series with an auto-encoder

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Probabilistic time series modeling in Python