274 Open source projects that are alternatives of or similar to Ipynotebook_machinelearning

Python library for Bayesian hyper-parameters optimization

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Fast and flexible Gaussian Process regression in Python

Probabilistic question-asking system: the program asks, the users answer. The minimal goal of the program is to identify what the user needs (a target), even if the user is not aware of the existence of such a thing/product/service.

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Relation Classification - SEMEVAL 2010 task 8 dataset

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Python package facilitating the use of Bayesian Deep Learning methods with Variational Inference for PyTorch

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Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more

This is a Project Page of 'Towards a complete 3D morphable model of the human head'

Jupyter Notebooks from the old UnsupervisedLearning.com (RIP) machine learning and statistics blog

Automatic feature engineering using deep learning and Bayesian inference using TensorFlow.

Solve and estimate Dynamic Stochastic General Equilibrium models (including the New York Fed DSGE)

Implementations of single and multi-ellipsoid nested sampling

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Stanマニュアルの日本語への翻訳プロジェクト

nessai: Nested Sampling with Artificial Intelligence

Implementation of random Fourier features for kernel method, like support vector machine and Gaussian process model

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Examples for Bayesian inference using DynamicHMC.jl and related packages.

Max-value Entropy Search for Efficient Bayesian Optimization

Hierarchical, multi-label topic modelling with LDA

A python module to detect stellar flares using Bayesian model comparison

Efficient, lightweight variational inference and approximation bounds

brms R package for Bayesian generalized multivariate non-linear multilevel models using Stan

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Useful tools for periodicity analysis in time series data.

Predicting Consumer Purchase intention using Twitter Data

A clustering tutorial with scikit-learn for beginners.

Repository of teaching materials, code, and data for my data analysis and machine learning projects.

No description or website provided.

Sleek implementations of the ZigZag, Boomerang and other assorted piecewise deterministic Markov processes for Markov Chain Monte Carlo including Sticky PDMPs for variable selection

UAI 2015. Kernel-based just-in-time learning for expectation propagation

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Bayesian tools for fitting molecular mechanics torsion parameters to quantum chemical data.

Full Bayesian Inference for Hidden Markov Models

Pure julia implementation of Multiple Affine Invariant Sampling for efficient Approximate Bayesian Computation

Multi-core BUGS for fast Bayesian inference of large hierarchical models

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K2 systematics correction using Gaussian processes

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Particle filtering and sequential parameter inference in Python

Cell and line magic for PGF/TikZ-to-SVG rendering in Jupyter notebooks

Bayesian Data Analysis demos for Python

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Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)