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22 search results found
H2o 3
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6,618
H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.
Hyperlearn
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1,387
2-2000x faster ML algos, 50% less memory usage, works on all hardware - new and old.
Pca Magic
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175
PCA that iteratively replaces missing data
Python_for_data_science
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129
python_for_data_science
Vizuka
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100
Explore high-dimensional datasets and how your algo handles specific regions.
Kaggle Houseprices
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88
Kaggle Kernel for House Prices competition https://www.kaggle.com/massquantity/all-you-need-i
Betaml.jl
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83
Beta Machine Learning Toolkit
Hyperspectral_image_analysis_simplified
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77
The repository contains the implementation of different machine learning techniques such as classification and clustering on Hyperspectral and Satellite Imagery.
Slik_python_package
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60
A data wrangling and modeling tool.
Data Science Learning
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32
📊 All of courses, assignments, exercises, mini-projects and books that I've done so far in the process of learning by myself Machine Learning and Data Science.
Zeta Learn
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27
zeta-lean: minimalistic python machine learning library built on top of numpy and matplotlib
Ppca_rs
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22
Python+Rust implementation of the Probabilistic Principal Component Analysis model
Ai Ml Unit 2
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16
Course Material for Artificial Intelligence and Machine Learning - Unit 2 @ Computer Science Dept, Sapienza
Projection Pursuit
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16
Code for performing various projection pursuit routines
Fscnmf
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16
An implementation of "Fusing Structure and Content via Non-negative Matrix Factorization for Embedding Information Networks".
Machine Learning Lecture Notes
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9
Lecture notes and codes for machine learning
Unsupervised_analysis
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9
A general purpose Snakemake workflow to perform unsupervised analyses (dimensionality reduction & cluster analysis) and visualizations of high-dimensional data.
Pca Principal Component Analysis
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7
Principal Component Analysis (PCA) is by far the most popular dimensionality reduction algorithm. First it identifies the hyperplane that lies closest to the data, and then it projects the data onto it.
Hapod
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7
HAPOD - Hierarchical Approximate Proper Orthogonal Decomposition
Skewedphillips
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6
Työttömyyden ennustamisen työkalu, joka hyödyntää kuluttajahintaindeksejä. Tool for predicting unemployment with consumer price indexes and machine learning.
Learning
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6
Evaluation metrics and essential machine learning for Haskell
Davil
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6
Python Multivariate Data Visualization Tool based on radial axes
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1-22 of 22 search results
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