Alternatives and similar repositories for IPyNotebook_MachineLearning:

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

• zalandoresearch / probrnn
  State space modeling with recurrent neural networks
  ☆44Updated 7 years ago
• franck-durand / tsboost
  Time Series Forecasting Framework
  ☆41Updated 2 years ago
• lacava / few
  a feature engineering wrapper for sklearn
  ☆51Updated 4 years ago
• alan-turing-institute / bocpdms
  ☆32Updated 6 years ago
• lawrennd / old_talks
  Talks from Neil Lawrence
  ☆54Updated last year
• thangbui / geepee
  A collection of Gaussian process models
  ☆30Updated 7 years ago
• strongio / quantile-regression-tensorflow
  Tensorflow implementation of deep quantile regression
  ☆76Updated 2 years ago
• PGM-Lab / InferPy
  InferPy: Deep Probabilistic Modeling with Tensorflow Made Easy
  ☆148Updated 8 months ago
• JackKelly / bayesianchangepoint
  An implementation of Adams & MacKay 2007 "Bayesian Online Changepoint Detection"
  ☆31Updated 10 years ago
• cangermueller / ppca
  Probabilistic Principal Component Analysis
  ☆61Updated 7 years ago
• FlorianWilhelm / bhm-at-scale
  🪜 Bayesian Hierarchical Models at Scale
  ☆52Updated 3 years ago
• cambridge-mlg / sghmc_dgp
  ☆28Updated 6 years ago
• fehiepsi / rethinking-pyro
  Statistical Rethinking with PyTorch and Pyro
  ☆163Updated 5 years ago
• junpenglao / Planet_Sakaar_Data_Science
  A colourful collection of codes and notebooks, like Planet Sakaar
  ☆55Updated last year
• vlad17 / runlmc
  Structurally efficient multi-output linearly coregionalized Gaussian Processes: it's tricky, tricky, tricky, tricky, tricky.
  ☆37Updated 2 years ago
• probcomp / trcrpm
  Temporally-reweighted Chinese restaurant process mixture models for multivariate time series
  ☆37Updated last year
• epfl-lasa / changepoint-detection
  Online Change-point Detection Algorithm for Multi-Variate Data: Applications on Human/Robot Demonstrations.
  ☆45Updated 7 years ago
• kasparmartens / NeuralProcesses
  Neural Processes implementation for 1D regression
  ☆65Updated 6 years ago
• ceshine / quantile-regression-tensorflow
  Implementations of Quantile Regression
  ☆28Updated 6 years ago
• CamDavidsonPilon / Python-Numerics
  Numerical machines in Python
  ☆94Updated 10 years ago
• fabsig / KTBoost
  A Python package which implements several boosting algorithms with different combinations of base learners, optimization algorithms, and …
  ☆63Updated 3 years ago
• parsing-science / pymc3_models
  ☆158Updated 2 years ago
• mathDR / abocpd
  Python implementation of "Adaptive Sequential Bayesian Change Point Detection" algorithm (Turner, et.al)
  ☆22Updated 5 years ago
• suriyadeepan / BayesianML
  Experiments in Bayesian Machine Learning
  ☆69Updated 5 years ago
• jmetzen / gp_extras
  Additional kernels that can be used with scikit-learn's Gaussian Process module
  ☆82Updated 8 months ago
• dfagnan / QuantileRandomForestRegressor
  Python Implementation of Quantile Random Forest Regression
  ☆12Updated 10 years ago
• RJT1990 / talks
  ☆12Updated 8 years ago
• fonnesbeck / PyMC3_DataScienceLA
  PyMC3 tutorial for DataScience LA (January 2017)
  ☆67Updated 6 years ago
• hstrey / Hidden-Markov-Models-pymc3
  Implementation of Hidden Markov Models in pymc3
  ☆60Updated 8 years ago
• nnikolaou / Cost-sensitive-Boosting-Tutorial
  Tutorial on cost-sensitive boosting and calibrated AdaMEC.
  ☆26Updated 7 years ago