Alternatives and similar repositories for TimeSeries:

Users that are interested in TimeSeries are comparing it to the libraries listed below

• maheshakya / Time-Series-Forcasting-with-Neural-Networks
  Using a multi-perception neural network perform time series forecasting. Here feed forward technique is used.
  ☆7Updated 11 years ago
• saber1988 / sentiment-analysis
  sentiment analysis using IMDB data set. The code uses tensorflow to implement a sequence2vec model
  ☆8Updated 8 years ago
• chriso / timeseries
  Time series analysis
  ☆42Updated 10 years ago
• skuenzli / time-series-analysis
  Contains tools for analyzing time-series data.
  ☆11Updated 11 years ago
• zygmuntz / kaggle-burn-cpu
  Code for the "Burn CPU, burn" competition at Kaggle. Uses Extreme Learning Machines and hyperopt.
  ☆33Updated 10 years ago
• ChenglongChen / Kaggle_The_Hunt_for_Prohibited_Content
  4th Place Solution for The Hunt for Prohibited Content Competition on Kaggle (http://www.kaggle.com/c/avito-prohibited-content)
  ☆28Updated 10 years ago
• amueller / sklearn_tutorial
  Slides for quick intro to machine learning with sklearn
  ☆66Updated 11 years ago
• zygmuntz / kaggle-blackbox
  Deep learning made easy
  ☆116Updated 10 years ago
• MKLab-ITI / news-popularity-prediction
  A set of methods that predict the future values of popularity indices for news posts using a variety of features.
  ☆33Updated 7 years ago
• ericchiang / cloudy-tweets
  Machine Learning solution for Kaggle.com's "Partly Sunny with a Chance of Hashtags"
  ☆27Updated 11 years ago
• zygmuntz / the-secret-of-the-big-guys
  k-means + a linear model = good results
  ☆55Updated 10 years ago
• glorotxa / DeepANN
  Theano based deep ANN learning code
  ☆38Updated 14 years ago
• dhwajraj / spark-text-tagger
  Script to perform dictionary based n-gram text tagging efficiently in apache spark
  ☆11Updated 8 years ago
• mike-perdide / scikit-learn-tutorial
  Applied Machine Learning in Python with scikit-learn
  ☆47Updated 14 years ago
• python-recsys / recsys-tutorial
  Recommender Systems in Depth: An introduction to Recommender Systems using Python and Crab
  ☆44Updated 11 years ago
• ankazhao / python-sparselda
  A Latent Dirichlet Allocation topic modeling package based on SparseLDA Gibbs Sampling inference algorithm
  ☆8Updated 11 years ago
• KirkHadley / SectorRotation
  RF + GBM + ARIMA/NN Hybrid ensemble for predicting 6-month returns for the 9 sector ETFs plus IYZ
  ☆24Updated 11 years ago
• nouiz / ccw_tutorial_theano
  Common Code Workflow tutorial on Theano
  ☆16Updated 9 years ago
• stober / dtw
  Dynamic Time Warping in Python
  ☆28Updated 12 years ago
• wangkobe88 / Mercury
  Mercury：Recommendation Engine Sandbox Using Movielens Dataset
  ☆8Updated 10 years ago
• dselivanov / word_embeddings
  Experiments on english wikipedia. GloVe and word2vec.
  ☆13Updated 9 years ago
• mblondel / ivalice
  Boosting and ensemble learning in Python.
  ☆54Updated 9 years ago
• brett-pplx / AMC
  Code for KDD 2014 paper "Mining Topics in Documents: Standing on the Shoulders of Big Data"
  ☆21Updated 9 years ago
• maxpumperla / neuralforecast
  Time Series Prediction: A Non Linear Approach with Neural Networks
  ☆34Updated 8 years ago
• alextp / pylda
  An implementation of gibbs sampling for Latent Dirichlet Allocation
  ☆30Updated 13 years ago
• MillionIntegrals / ESL
  Algorithms from the book "Elements of Statistical Learning", implemented in Python
  ☆10Updated 10 years ago
• dmcgarry / Default_Loan_Prediction
  Code for Kaggle's Default Loan Prediction - Imperial College London challenge.
  ☆29Updated 11 years ago
• socialsensor / storm-focused-crawler
  Collects multimedia content shared through social networks.
  ☆19Updated 10 years ago
• brendano / OConnor_IREvents_ACL2013
  Replication software, data, and supplementary materials for the paper: O'Connor, Stewart and Smith, ACL-2013, "Learning to Extract Intern…
  ☆26Updated 4 years ago
• yjernite / DeepCRF
  A suite of tools for sequence tagging, including regular and "deep" CRF, as well as convolutional and recurrent neural networks.
  ☆9Updated 9 years ago