770 Open source projects that are alternatives of or similar to data-science-learning

scikit-learn机器学习库中文文档翻译项目

Learn how to use Kinesis Firehose, AWS Glue, S3, and Amazon Athena by streaming and analyzing reddit comments in realtime. 100-200 level tutorial.

Samples and Tools for Windows ML.

Research data analytics tutorials using the Dimensions Analytics API

An open source python library for automated feature engineering

Kaggle 120种狗分类，Gluon实现

A scikit-learn compatible library for anomaly detection

Modern port of Melanie Mitchell's and Douglas Hofstadter's Copycat

A graph-based functional API for building complex scikit-learn pipelines.

머신러닝/딥러닝(PyTorch, TensorFlow) 전용 도커입니다. 한글 폰트, 한글 자연어처리 패키지(konlpy), 형태소 분석기, Timezone 등의 설정 등을 추가 하였습니다.

Portfolio of data science projects completed by me for academic, self learning, and hobby purposes.

Using machine learning on your anki collection to enhance the scheduling via semantic clustering and semantic similarity

REST web service for the true real-time scoring (<1 ms) of Scikit-Learn, R and Apache Spark models

A collection of full-stack resources for programmers.

Survival analysis built on top of scikit-learn

This is our team's solution report, which achieves top 10% (305/3307) in this competition.

A machine learning package for streaming data in Python. The other ancestor of River.

A simple app which shows the lastest movies trailers based on different genres developed using SwiftUI.

ONNXMLTools enables conversion of models to ONNX

Machine learning in Python with scikit-learn MOOC

Concepts and ideas for the GNOME desktop

Extra blocks for scikit-learn pipelines.

Compilation of good Kaggle Kernels.

🤖⚡️ scikit-learn tips

XAI Tutorial for the Explainable AI track in the ALPS winter school 2021

50% faster, 50% less RAM Machine Learning. Numba rewritten Sklearn. SVD, NNMF, PCA, LinearReg, RidgeReg, Randomized, Truncated SVD/PCA, CSR Matrices all 50+% faster

custom human activity recognition modules by pose estimation and cascaded inference using sklearn API

Comparing FC VAE / FCN VAE / PCA / UMAP on MNIST / FMNIST

Wavelet scattering transforms in Python with GPU acceleration

🍊 📊 💡 Orange: Interactive data analysis

A unified framework for machine learning with time series

python library implementing ensemble methods for regression, classification and visualisation tools including Voronoi tesselations.

sktime companion package for deep learning based on TensorFlow

A drop-in replacement for Scikit-Learn’s GridSearchCV / RandomizedSearchCV -- but with cutting edge hyperparameter tuning techniques.

libfaceid is a research framework for prototyping of face recognition solutions. It seamlessly integrates multiple detection, recognition and liveness models w/ speech synthesis and speech recognition.

My textbook for teaching Machine Learning

This repository contains Ipython notebooks and datasets for the data analytics youtube tutorials on The Semicolon.

Machine Learning and NLP: Text Classification using python, scikit-learn and NLTK

A scikit-learn compatible library for graph kernels

ThotKeeper — cross-platform personal daily journaling

Natural Intelligence is still a pretty good idea.

Machine Learning Containers for NVIDIA Jetson and JetPack-L4T

A wine recommender system tutorial using Python technologies such as Django, Pandas, or Scikit-learn, and others such as Bootstrap.

<Do it! 딥러닝 입문> 도서의 주피터 노트북

Automatically Visualize any dataset, any size with a single line of code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upon Request.

MNIST digit classification with scikit-learn and Support Vector Machine (SVM) algorithm.

Zeek Analysis Tools (ZAT): Processing and analysis of Zeek network data with Pandas, scikit-learn, Kafka and Spark

skrobot is a Python module for designing, running and tracking Machine Learning experiments / tasks. It is built on top of scikit-learn framework.

based on "Hands-On Machine Learning with Scikit-Learn & TensorFlow" (O'Reilly, Aurelien Geron)

Feature engineering is the process of using domain knowledge to extract features from raw data via data mining techniques. These features can be used to improve the performance of machine learning algorithms. Feature engineering can be considered as applied machine learning itself.

AutoGluon: AutoML for Text, Image, and Tabular Data

Content on tips, tricks, advice, practices for naming things in in software/technology

Kaggle | 14th place solution for TGS Salt Identification Challenge

Formed trajectories of sets of points.Experimented on finding similarities between trajectories based on DTW (Dynamic Time Warping) and LCSS (Longest Common SubSequence) algorithms.Modeled trajectories as strings based on a Grid representation.Benchmarked KNN, Random Forest, Logistic Regression classification algorithms to classify efficiently t…

Small Docker image with Python Machine Learning tools (~180MB) https://hub.docker.com/r/frolvlad/alpine-python-machinelearning/

Start writing machine learning code in just 10 hours

Public reusable components for Polyaxon

Introduction to Statistical Learning with R을 Python으로

A collection of Machine Learning algorithms written from sctrach.

Automatically Build Multiple ML Models with a Single Line of Code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upon Request.