Docker Alpine Python MachinelearningSmall Docker image with Python Machine Learning tools (~180MB) https://hub.docker.com/r/frolvlad/alpine-python-machinelearning/
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kdd99-scikitSolutions to kdd99 dataset with Decision tree and Neural network by scikit-learn
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ml-bookCodice sorgente ed Errata Corrige del mio libro "A tu per tu col Machine Learning"
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Islr With PythonIntroduction to Statistical Learning with R을 Python으로
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booksA collection of online books for data science, computer science and coding!
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Jetson ContainersMachine Learning Containers for NVIDIA Jetson and JetPack-L4T
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A-Detector⭐ An anomaly-based intrusion detection system.
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Mlatimperial2017Materials for the course of machine learning at Imperial College organized by Yandex SDA
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RobustPCANo description or website provided.
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doubleml-for-pyDoubleML - Double Machine Learning in Python
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ModalA modular active learning framework for Python
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ray tutorialAn introductory tutorial about leveraging Ray core features for distributed patterns.
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machine-learning-capstone-projectThis is the final project for the Udacity Machine Learning Nanodegree: Predicting article retweets and likes based on the title using Machine Learning
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Metric LearnMetric learning algorithms in Python
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dbt-ml-preprocessingA SQL port of python's scikit-learn preprocessing module, provided as cross-database dbt macros.
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SelfrandoFunction order shuffling to defend against ROP and other types of code reuse
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NimbusML-SamplesSamples for NimbusML, a Python machine learning package providing simple interoperability between ML.NET and scikit-learn components.
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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.
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converseConversational text Analysis using various NLP techniques
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Fraud DetectionCredit Card Fraud Detection using ML: IEEE style paper + Jupyter Notebook
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sklearn-oblique-treea python interface to OC1 and other oblique decision tree implementations
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hubPublic reusable components for Polyaxon
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MlkatasA series of self-correcting challenges for practicing your Machine Learning and Deep Learning skills
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PyRCNA Python 3 framework for Reservoir Computing with a scikit-learn-compatible API.
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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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Ds and ml projectsData Science & Machine Learning projects and tutorials in python from beginner to advanced level.
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Discover CookbookThe NumFOCUS DISCOVER Cookbook (Diverse & Inclusive Spaces and Conferences: Overall Vision and Essential Resources). A guide for organizing more diverse and inclusive events and conferences, produced by the NumFOCUS Diversity & Inclusion in Scientific Computing (DISC) Program, with support from the Moore Foundation.
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nba-analysisUsing machine learning libraries to analyze NBA data
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Spark Sklearn(Deprecated) Scikit-learn integration package for Apache Spark
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MachineLearningImplementations of machine learning algorithm by Python 3
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scitimeTraining time estimation for scikit-learn algorithms
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ImlКурс "Введение в машинное обучение" (ВМК, МГУ имени М.В. Ломоносова)
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clinicaSoftware platform for clinical neuroimaging studies
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Sklearn OnnxConvert scikit-learn models and pipelines to ONNX
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Machine Learningnotebooks with example for machine learning examples
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data-science-learning📊 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.
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Awesome CultureA curated list of awesome thought on tech culture. Inspired by the various awesome-* projects
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Sklearn PorterTranspile trained scikit-learn estimators to C, Java, JavaScript and others.
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Statistical-Learning-using-RThis is a Statistical Learning application which will consist of various Machine Learning algorithms and their implementation in R done by me and their in depth interpretation.Documents and reports related to the below mentioned techniques can be found on my Rpubs profile.
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face ratingFace/Beauty Rating with both the traditional ML approaches and Convolutional Neural Network Approach
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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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go-ml-benchmarks⏱ Benchmarks of machine learning inference for Go
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concentrationMetricsA python library for the computation of various concentration, inequality and diversity indices
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Qlik Py ToolsData Science algorithms for Qlik implemented as a Python Server Side Extension (SSE).
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AutovizAutomatically Visualize any dataset, any size with a single line of code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upon Request.
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