377 Open source projects that are alternatives of or similar to sklearn-oblique-tree

Algorithmic trading using machine learning.

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A gentle introduction to machine learning: data handling, linear regression, naive bayes, clustering

Boosted trees in Julia

도서 "[개정판] 파이썬 라이브러리를 활용한 머신 러닝"의 주피터 노트북과 코드입니다.

2019년 민족사관고등학교 졸업 프로젝트

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Quick-Data-Science-Experiments

Aircraft engine failure prediction model

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simple Echo State Networks integrated with scikit-learn

Machine Learning in .NET Core.

Data Science algorithms and topics that you must know. (Newly Designed) Recommender Systems, Decision Trees, K-Means, LDA, RFM-Segmentation, XGBoost in Python, R, and Scala.

도서 "핸즈온 머신러닝"의 예제와 연습문제를 담은 주피터 노트북입니다.

Automatic machine learning for tabular data. ⚡🔥⚡

machine_learning_examples

Helm charts for creating reproducible and maintainable deployments of Polyaxon with Kubernetes.

中文文本分类实践，基于搜狗新闻语料库，采用传统机器学习方法以及预训练模型等方法

A decision tree to help you decide on the right AWS compute service for your needs.

A comprehensive dimensional reduction framework to recover the latent topology from high-dimensional data.

Pedestrian Detection using Non Maximum Suppression

python codes for remote sensing applications will be uploaded here. I will try to teach everything I learn during my projects in here.

A complete one stop solution for all the problems of Rural area people. 👩🏻‍🌾

<Do it! 딥러닝 입문> 도서의 주피터 노트북

Dockerize and deploy machine learning model as REST API using Flask

(Python) transform a document-term matrix to an Okapi/BM25 representation

Jupyter Notebooks and miscellaneous

Predict materials properties using only the composition information!

Implementations of machine learning algorithm by Python 3

Code for determining optimal number of clusters for K-means algorithm using the 'elbow criterion'

A Python 3 framework for Reservoir Computing with a scikit-learn-compatible API.

A Python package for fitting Quinlan's Cubist regression model

A clustering tutorial with scikit-learn for beginners.

機器學習: Python

NYC scikit-learn sprint (Sep 2018)

Ruby Scoring API for PMML

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Solution of the Titanic Kaggle competition

My textbook for teaching Machine Learning

NYC WiMLDS scikit-learn open source sprint (Aug 24, 2019)

A library to parse and convert PMML models into Scikit-learn estimators.

Data Mining algorithms for IDMW632C course at IIIT Allahabad, 6th semester

Complete Conjugation of any Verb using Machine Learning for French, Spanish, Portuguese, Italian and Romanian

Machine Learning for Spot Prices

Polyaxon Core Client & CLI to streamline MLOps

Predicting Google’s stock price using regression

In this work, we propose a deterministic version of Local Interpretable Model Agnostic Explanations (LIME) and the experimental results on three different medical datasets shows the superiority for Deterministic Local Interpretable Model-Agnostic Explanations (DLIME).

📊 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.

This repository is a recommended track, designed to get started with Machine Learning.

Using machine learning libraries to analyze NBA data

https://dodiku.github.io/audio_noise_clustering/results/ ==> An experiment with a variety of clustering (and clustering-like) techniques to reduce noise on an audio speech recording.

Python for chemoinformatics

12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all

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