pipelinePipelineAI Kubeflow Distribution
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Tune SklearnA drop-in replacement for Scikit-Learn’s GridSearchCV / RandomizedSearchCV -- but with cutting edge hyperparameter tuning techniques.
Stars: ✭ 241 (+1908.33%)
scitimeTraining time estimation for scikit-learn algorithms
Stars: ✭ 119 (+891.67%)
imbalanced-ensembleClass-imbalanced / Long-tailed ensemble learning in Python. Modular, flexible, and extensible. | 模块化、灵活、易扩展的类别不平衡/长尾机器学习库
Stars: ✭ 199 (+1558.33%)
Amazing Feature EngineeringFeature 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.
Stars: ✭ 218 (+1716.67%)
Artificial Intelligence Deep Learning Machine Learning TutorialsA comprehensive list of Deep Learning / Artificial Intelligence and Machine Learning tutorials - rapidly expanding into areas of AI/Deep Learning / Machine Vision / NLP and industry specific areas such as Climate / Energy, Automotives, Retail, Pharma, Medicine, Healthcare, Policy, Ethics and more.
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ml-restREST API (and possible UI) for Machine Learning workflows
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Jetson ContainersMachine Learning Containers for NVIDIA Jetson and JetPack-L4T
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scikit-hyperbandA scikit-learn compatible implementation of hyperband
Stars: ✭ 68 (+466.67%)
pygramsExtracts key terminology (n-grams) from any large collection of documents (>1000) and forecasts emergence
Stars: ✭ 52 (+333.33%)
ASD-ML-APIThis project has 3 goals: To find out the best machine learning pipeline for predicting ASD cases using genetic algorithms, via the TPOT library. (Classification Problem) Compare the accuracy of the accuracy of the determined pipeline, with a standard Naive-Bayes classifier. Saving the classifier as an external file, and use this file in a Flask…
Stars: ✭ 14 (+16.67%)
go-ml-benchmarks⏱ Benchmarks of machine learning inference for Go
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lending-clubApplying machine learning to predict loan charge-offs on LendingClub.com
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Orange3🍊 📊 💡 Orange: Interactive data analysis
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ML-TrackThis repository is a recommended track, designed to get started with Machine Learning.
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Text ClassificationMachine Learning and NLP: Text Classification using python, scikit-learn and NLTK
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sklearn-matlabMachine learning in Matlab using scikit-learn syntax
Stars: ✭ 27 (+125%)
rezonanceContent Based Music Recommendation Service
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Auto vimlAutomatically Build Multiple ML Models with a Single Line of Code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upon Request.
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Movie-Recommendation-ChatbotMovie Recommendation Chatbot provides information about a movie like plot, genre, revenue, budget, imdb rating, imdb links, etc. The model was trained with Kaggle’s movies metadata dataset. To give a recommendation of similar movies, Cosine Similarity and TFID vectorizer were used. Slack API was used to provide a Front End for the chatbot. IBM W…
Stars: ✭ 33 (+175%)
HummingbirdHummingbird compiles trained ML models into tensor computation for faster inference.
Stars: ✭ 2,704 (+22433.33%)
TextClassification基于scikit-learn实现对新浪新闻的文本分类,数据集为100w篇文档,总计10类,测试集与训练集1:1划分。分类算法采用SVM和Bayes,其中Bayes作为baseline。
Stars: ✭ 86 (+616.67%)
100DaysOfMLCodeI am taking up the #100DaysOfMLCode Challenge 😎
Stars: ✭ 12 (+0%)
nlp workshop odsc europe20Extensive tutorials for the Advanced NLP Workshop in Open Data Science Conference Europe 2020. We will leverage machine learning, deep learning and deep transfer learning to learn and solve popular tasks using NLP including NER, Classification, Recommendation \ Information Retrieval, Summarization, Classification, Language Translation, Q&A and T…
Stars: ✭ 127 (+958.33%)
intro-to-mlA basic introduction to machine learning (one day training).
Stars: ✭ 15 (+25%)
emoji-prediction🤓🔮🔬 Emoji prediction from a text using machine learning
Stars: ✭ 41 (+241.67%)
TF-Speech-Recognition-Challenge-SolutionSource code of the model used in Tensorflow Speech Recognition Challenge (https://www.kaggle.com/c/tensorflow-speech-recognition-challenge). The solution ranked in top 5% in private leaderboard.
Stars: ✭ 58 (+383.33%)
notebooksA docker-based starter kit for machine learning via jupyter notebooks. Designed for those who just want a runtime environment and get on with machine learning. Docker tags:
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RobustPCANo description or website provided.
Stars: ✭ 15 (+25%)
kenchiA scikit-learn compatible library for anomaly detection
Stars: ✭ 36 (+200%)
pycobrapython library implementing ensemble methods for regression, classification and visualisation tools including Voronoi tesselations.
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face ratingFace/Beauty Rating with both the traditional ML approaches and Convolutional Neural Network Approach
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PorndetectorPorn images detector with python, tensorflow, scikit-learn and opencv.
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cliPolyaxon Core Client & CLI to streamline MLOps
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Igela delightful machine learning tool that allows you to train, test, and use models without writing code
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ElandPython Client and Toolkit for DataFrames, Big Data, Machine Learning and ETL in Elasticsearch
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skrobotskrobot is a Python module for designing, running and tracking Machine Learning experiments / tasks. It is built on top of scikit-learn framework.
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scikit-learn-intelexIntel(R) Extension for Scikit-learn is a seamless way to speed up your Scikit-learn application
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Voice4RuralA complete one stop solution for all the problems of Rural area people. 👩🏻🌾
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SphereclusterClustering routines for the unit sphere
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PredictionAPITutorial on deploying machine learning models to production
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website-fingerprintingDeanonymizing Tor or VPN users with website fingerprinting and machine learning.
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Trajectory-Analysis-and-Classification-in-Python-Pandas-and-Scikit-LearnFormed 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…
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verbeccComplete Conjugation of any Verb using Machine Learning for French, Spanish, Portuguese, Italian and Romanian
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dlime experimentsIn 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).
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audio noise clusteringhttps://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.
Stars: ✭ 24 (+100%)
ml webappExplore machine learning models. Leveraging scikit-learn's models and exposing their behaviour through API
Stars: ✭ 29 (+141.67%)
hubPublic reusable components for Polyaxon
Stars: ✭ 8 (-33.33%)