Python Extreme Learning Machine (ELM) is a machine learning technique used for classification/regression tasks.
Bayesian Modeling and Computation in Python Open access and Code This repository contains the open access version of the text and the code examples in
Unsupervised-Machine-Learning Flat Clustering K-Means clusternig example with Python and Scikit-learn Flat clustering Clustering algorithms group a se
This is a TensorFlow implementation of an arbitrary order (=2) Factorization Machine based on paper Factorization Machines with libFM. It supports: d
Data-centric machine learning powered by DaCe
Using PySpark we can process data from Hadoop HDFS, AWS S3, and many file systems. PySpark also is used to process real-time data using Streaming and
LRM-Squannacook Input data for generating stochastic streamflows are observed and simulated timeseries of streamflow. their format needs to be CSV wit
vortex-particles-method-2d vortex particles for simulating smoke in 2d -vortexparticles_s
timemachines Autonomous, univariate, k-step ahead time-series forecasting functions assigned Elo ratings You can: Use some of the functionality of a s
🤖 Interactive Machine Learning experiments: 🏋️models training + 🎨models demo
MLProject_01 This project impelemented for midterm of the Machine Learning #Zoomcamp #Alexey Grigorev Context Dataset English question data set file F
Data Science on AWS - O'Reilly Book Get the book on Amazon.com Book Outline Quick Start Workshop (4-hours) In this quick start hands-on workshop, you
BioPy is a collection (in-progress) of biologically-inspired algorithms written in Python. Some of the algorithms included are mor
Diabetes Prediction with Logistic Regression Exploratory Data Analysis Data Preprocessing Model & Prediction Model Evaluation Model Validation: Holdou
Domino Research This repo contains projects under active development by the Domino R&D team. We build tools that help Data Scientists and ML engineers
MosaicML Composer MosaicML Composer contains a library of methods, and ways to compose them together for more efficient ML training. We aim to ease th
hexhamming What does it do? This module performs a fast bitwise hamming distance of two hexadecimal strings. This looks like: DEADBEEF = 1101111010101
Neighbourhood Retrieval with Distance Correlation Assign Pseudo class labels to datapoints in the latent space. NNDC is a slim wrapper around FAISS. N
PySpark-Bank-Churn Surname: corresponds to the record (row) number and has no effect on the output. CreditScore: contains random values and has no eff
2021 Machine Learning Security Evasion Competition This repository contains code samples for the 2021 Machine Learning Security Evasion Competition. P
TensorFlowOnSpark TensorFlowOnSpark brings scalable deep learning to Apache Hadoop and Apache Spark clusters. By combining salient features from the T
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