Vehicle DetectionVehicle detection using machine learning and computer vision techniques for Udacity's Self-Driving Car Engineer Nanodegree.
Stars: ✭ 1,093 (-67.22%)
Ml Fraud DetectionCredit card fraud detection through logistic regression, k-means, and deep learning.
Stars: ✭ 117 (-96.49%)
100daysofmlcodeMy journey to learn and grow in the domain of Machine Learning and Artificial Intelligence by performing the #100DaysofMLCode Challenge.
Stars: ✭ 146 (-95.62%)
AulasAulas da Escola de Inteligência Artificial de São Paulo
Stars: ✭ 166 (-95.02%)
InfiniteboostInfiniteBoost: building infinite ensembles with gradient descent
Stars: ✭ 180 (-94.6%)
Machinelearning ng吴恩达机器学习coursera课程,学习代码(2017年秋) The Stanford Coursera course on MachineLearning with Andrew Ng
Stars: ✭ 181 (-94.57%)
ClandmarkOpen Source Landmarking Library
Stars: ✭ 204 (-93.88%)
machine learning courseArtificial intelligence/machine learning course at UCF in Spring 2020 (Fall 2019 and Spring 2019)
Stars: ✭ 47 (-98.59%)
100 Days Of Ml CodeA day to day plan for this challenge. Covers both theoritical and practical aspects
Stars: ✭ 172 (-94.84%)
Recsys core[电影推荐系统] Based on the movie scoring data set, the movie recommendation system is built with FM and LR as the core(基于爬取的电影评分数据集,构建以FM和LR为核心的电影推荐系统).
Stars: ✭ 245 (-92.65%)
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…
Stars: ✭ 41 (-98.77%)
AutofeatLinear Prediction Model with Automated Feature Engineering and Selection Capabilities
Stars: ✭ 178 (-94.66%)
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。
Stars: ✭ 85 (-97.45%)
srqmAn introductory statistics course for social scientists, using Stata
Stars: ✭ 43 (-98.71%)
goscoreGo Scoring API for PMML
Stars: ✭ 85 (-97.45%)
AIML-ProjectsProjects I completed as a part of Great Learning's PGP - Artificial Intelligence and Machine Learning
Stars: ✭ 85 (-97.45%)
Python-AndrewNgMLPython implementation of Andrew Ng's ML course projects
Stars: ✭ 24 (-99.28%)
AilearningAiLearning: 机器学习 - MachineLearning - ML、深度学习 - DeepLearning - DL、自然语言处理 NLP
Stars: ✭ 32,316 (+869.29%)
rfvisA tool for visualizing the structure and performance of Random Forests 🌳
Stars: ✭ 20 (-99.4%)
Machine-learningThis repository will contain all the stuffs required for beginners in ML and DL do follow and star this repo for regular updates
Stars: ✭ 27 (-99.19%)
ClassifierToolboxA MATLAB toolbox for classifier: Version 1.0.7
Stars: ✭ 72 (-97.84%)
MachineLearningImplementations of machine learning algorithm by Python 3
Stars: ✭ 16 (-99.52%)
info-retrievalInformation Retrieval in High Dimensional Data (class deliverables)
Stars: ✭ 33 (-99.01%)
SGDLibraryMATLAB/Octave library for stochastic optimization algorithms: Version 1.0.20
Stars: ✭ 165 (-95.05%)
amazon-reviewsSentiment Analysis & Topic Modeling with Amazon Reviews
Stars: ✭ 26 (-99.22%)
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.
Stars: ✭ 42 (-98.74%)
RgtsvmThe R package for SVM with GPU architecture based on the GTSVM software
Stars: ✭ 27 (-99.19%)
handson-ml도서 "핸즈온 머신러닝"의 예제와 연습문제를 담은 주피터 노트북입니다.
Stars: ✭ 285 (-91.45%)
zAnalysiszAnalysis是基于Pascal语言编写的大型统计学开源库
Stars: ✭ 52 (-98.44%)
SentimentAnalysis(BOW, TF-IDF, Word2Vec, BERT) Word Embeddings + (SVM, Naive Bayes, Decision Tree, Random Forest) Base Classifiers + Pre-trained BERT on Tensorflow Hub + 1-D CNN and Bi-Directional LSTM on IMDB Movie Reviews Dataset
Stars: ✭ 40 (-98.8%)
yggdrasil-decision-forestsA collection of state-of-the-art algorithms for the training, serving and interpretation of Decision Forest models.
Stars: ✭ 156 (-95.32%)
mnist-challengeMy solution to TUM's Machine Learning MNIST challenge 2016-2017 [winner]
Stars: ✭ 68 (-97.96%)
MLDay18Material from "Random Forests and Gradient Boosting Machines in R" presented at Machine Learning Day '18
Stars: ✭ 15 (-99.55%)
NMFADMMA sparsity aware implementation of "Alternating Direction Method of Multipliers for Non-Negative Matrix Factorization with the Beta-Divergence" (ICASSP 2014).
Stars: ✭ 39 (-98.83%)
VBLinLogitVariational Bayes linear and logistic regression
Stars: ✭ 25 (-99.25%)
NIDS-Intrusion-DetectionSimple Implementation of Network Intrusion Detection System. KddCup'99 Data set is used for this project. kdd_cup_10_percent is used for training test. correct set is used for test. PCA is used for dimension reduction. SVM and KNN supervised algorithms are the classification algorithms of project. Accuracy : %83.5 For SVM , %80 For KNN
Stars: ✭ 45 (-98.65%)
AdaptiveRandomForestRepository for the AdaptiveRandomForest algorithm implemented in MOA 2016-04
Stars: ✭ 28 (-99.16%)
ML-CourseraThis repository contains all the programming exercises in Python for the Coursera course called "Machine Learning" by Adjunct Professor Andrew Ng at Stanford University.
Stars: ✭ 66 (-98.02%)
Clustering-in-PythonClustering methods in Machine Learning includes both theory and python code of each algorithm. Algorithms include K Mean, K Mode, Hierarchical, DB Scan and Gaussian Mixture Model GMM. Interview questions on clustering are also added in the end.
Stars: ✭ 27 (-99.19%)