LidongZhang1222

LidongZhang1222's Stars

• yzhao062/pyod

  A Python Library for Outlier and Anomaly Detection, Integrating Classical and Deep Learning Techniques

  Language:Python8.7k1463391.4k

• yzhao062/anomaly-detection-resources

  Anomaly detection related books, papers, videos, and toolboxes

  Language:Python8.5k287221.8k

• jaungiers/LSTM-Neural-Network-for-Time-Series-Prediction

  LSTM built using Keras Python package to predict time series steps and sequences. Includes sin wave and stock market data

  Language:Python4.9k253882k

• susanli2016/Machine-Learning-with-Python

  Python code for common Machine Learning Algorithms

  Language:Jupyter Notebook4.4k269374.8k

• MorvanZhou/Tensorflow-Tutorial

  Tensorflow tutorial from basic to hard, 莫烦Python 中文AI教学

  Language:Python4.3k259231.9k

• rob-med/awesome-TS-anomaly-detection

  List of tools & datasets for anomaly detection on time-series data.

  3k10812454

• jiesutd/NCRFpp

  NCRF++, a Neural Sequence Labeling Toolkit. Easy use to any sequence labeling tasks (e.g. NER, POS, Segmentation). It includes character LSTM/CNN, word LSTM/CNN and softmax/CRF components.

  Language:Python1.9k60172446

• chickenbestlover/RNN-Time-series-Anomaly-Detection

  RNN based Time-series Anomaly detector model implemented in Pytorch.

  Language:Python1.2k3752317

• nivu/ai_all_resources

  A curated list of Best Artificial Intelligence Resources

  Language:Jupyter Notebook1.1k331267

• guillaume-chevalier/seq2seq-signal-prediction

  Signal forecasting with a Sequence-to-Sequence (seq2seq) Recurrent Neural Network (RNN) model in TensorFlow - Guillaume Chevalier

  Language:Jupyter Notebook1.1k4117293

• lkulowski/LSTM_encoder_decoder

  Build a LSTM encoder-decoder using PyTorch to make sequence-to-sequence prediction for time series data

  Language:Python3921887

• chen0040/keras-anomaly-detection

  Anomaly detection implemented in Keras

  Language:Python374255155

• Marcnuth/AnomalyDetection

  Twitter's Anomaly Detection in Pure Python

  Language:Python309212477

• MBKraus/Predicting_real_estate_prices_using_scikit-learn

  Predicting Amsterdam house / real estate prices using Ordinary Least Squares-, XGBoost-, KNN-, Lasso-, Ridge-, Polynomial-, Random Forest-, and Neural Network MLP Regression (via scikit-learn)

  Language:Python15915152

• Ankit-Kumar-Saini/Coursera_Deep_Learning_Specialization

  Implementation of Logistic Regression, MLP, CNN, RNN & LSTM from scratch in python. Training of deep learning models for image classification, object detection, and sequence processing (including transformers implementation) in TensorFlow.

  Language:Jupyter Notebook932561

• adityatb/noise-reduction-using-rnn

  Implements python programs to train and test a Recurrent Neural Network with Tensorflow

  Language:Python712325

• LopezGG/Sequence-Labelling

  Implementing , learning and re implementing "End-to-end Sequence Labeling via Bi-directional LSTM-CNNs-CRF" in keras

  Language:Python716443

• PatientEz/Multidimensional-time-series-prediction-

  Multidimensional Time Series Prediction by using LSTM

  Language:Python563018

• jefkine/zeta-learn

  zeta-lean: minimalistic python machine learning library built on top of numpy and matplotlib

  Language:Python36146

• abr-98/Stock_prediction_approach_modified

  A python based project to predict values based on RNN and Regression

  Language:Jupyter Notebook203015

• DavideRoznowicz/Stock-Transformer

  Whole-system multidimensional financial time series prediction and simulation from timestamped prices only.

  Language:Python6102

• elch10/anomaly-detection

  Change-point and anomaly detection in multidimensional time series

  Language:Jupyter Notebook6206

• faizalcorleone7/Data-Mining

  Predicts opening stock prices of 469 S&P companies. Uses five different datasets merged into one using the date column. Three regression techniques are used and also reinforcement learning is used among these algorithms to determine weights among these regressor predictions. Accuracy for each company on an average is 97%.

  Language:Python5101

• nghiahuynh-ai/Applying-Machine-learning-methods-for-petrolelum-production-rate-prediction

  linear regression, SVR, RNN, LSTM, GRU, python

  Language:Python4101

• wjdghks950/DeepLearning_py

  Contains codes for Deep RNN, CNN models; including regression models in Python 3.6.1

  Language:Python2100

• changweiwangisme/skiller

  this is a library for multidimensional time sequence learning and prediction

  Language:Python110

• emaballarin/financial-wholenamycs

  Whole-system multidimensional financial time series prediction and simulation from timestamped prices only (attempt of)

  Language:Python120