Machine-Learning-ModelsIn This repository I made some simple to complex methods in machine learning. Here I try to build template style code.
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Mylearnmachine learning algorithm
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models-by-exampleBy-hand code for models and algorithms. An update to the 'Miscellaneous-R-Code' repo.
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SGDLibraryMATLAB/Octave library for stochastic optimization algorithms: Version 1.0.20
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cobraA Python package to build predictive linear and logistic regression models focused on performance and interpretation
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srqmAn introductory statistics course for social scientists, using Stata
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Dat8General Assembly's 2015 Data Science course in Washington, DC
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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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Fuku MlSimple machine learning library / 簡單易用的機器學習套件
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Deep Math Machine Learning.aiA blog which talks about machine learning, deep learning algorithms and the Math. and Machine learning algorithms written from scratch.
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BrihaspatiCollection of various implementations and Codes in Machine Learning, Deep Learning and Computer Vision ✨💥
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GDLibraryMatlab library for gradient descent algorithms: Version 1.0.1
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Isl PythonSolutions to labs and excercises from An Introduction to Statistical Learning, as Jupyter Notebooks.
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Tensorflow BookAccompanying source code for Machine Learning with TensorFlow. Refer to the book for step-by-step explanations.
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25daysinmachinelearningI will update this repository to learn Machine learning with python with statistics content and materials
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MlA set of machine learning experiments in Clojure
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Machine Learning ModelsDecision Trees, Random Forest, Dynamic Time Warping, Naive Bayes, KNN, Linear Regression, Logistic Regression, Mixture Of Gaussian, Neural Network, PCA, SVD, Gaussian Naive Bayes, Fitting Data to Gaussian, K-Means
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Machine learningEstudo e implementação dos principais algoritmos de Machine Learning em Jupyter Notebooks.
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Python-AndrewNgMLPython implementation of Andrew Ng's ML course projects
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Deeplearning.ai该存储库包含由deeplearning.ai提供的相关课程的个人的笔记和实现代码。
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machine learning courseArtificial intelligence/machine learning course at UCF in Spring 2020 (Fall 2019 and Spring 2019)
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Handwritten-Digits-Classification-Using-KNN-Multiclass Perceptron-SVM🏆 A Comparative Study on Handwritten Digits Recognition using Classifiers like K-Nearest Neighbours (K-NN), Multiclass Perceptron/Artificial Neural Network (ANN) and Support Vector Machine (SVM) discussing the pros and cons of each algorithm and providing the comparison results in terms of accuracy and efficiecy of each algorithm.
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dominance-analysisThis package can be used for dominance analysis or Shapley Value Regression for finding relative importance of predictors on given dataset. This library can be used for key driver analysis or marginal resource allocation models.
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Machine-learningThis repository will contain all the stuffs required for beginners in ML and DL do follow and star this repo for regular updates
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regression-wasmTesting doing basic regression with web assembly
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ml-modelsMachine Learning Procedures and Functions for Neo4j
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scHPFSingle-cell Hierarchical Poisson Factorization
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ARM-gradientLow-variance, efficient and unbiased gradient estimation for optimizing models with binary latent variables. (ICLR 2019)
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abessFast Best-Subset Selection Library
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VisualMLInteractive Visual Machine Learning Demos.
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bruceR📦 BRoadly Useful Convenient and Efficient R functions that BRing Users Concise and Elegant R data analyses.
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ICC-2019-WC-predictionPredicting the winner of 2019 cricket world cup using random forest algorithm
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BCESPython module for performing linear regression for data with measurement errors and intrinsic scatter
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Market-Mix-ModelingMarket Mix Modelling for an eCommerce firm to estimate the impact of various marketing levers on sales
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mnist-challengeMy solution to TUM's Machine Learning MNIST challenge 2016-2017 [winner]
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TotalLeastSquares.jlSolve many kinds of least-squares and matrix-recovery problems
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ML-Experiments整理记录本人担任课程助教设计的四个机器学习实验,主要涉及简单的线性回归、朴素贝叶斯分类器、支持向量机、CNN做文本分类。内附实验指导书、讲解PPT、参考代码,欢迎各位码友讨论交流。
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sparserega collection of modern sparse (regularized) linear regression algorithms.
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brglm2Estimation and inference from generalized linear models using explicit and implicit methods for bias reduction
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