123 Open source projects that are alternatives of or similar to tf-example-models

In This repository I made some simple to complex methods in machine learning. Here I try to build template style code.

Heart Disease prediction using 5 algorithms

Estimation and inference from generalized linear models using explicit and implicit methods for bias reduction

Matlab library for gradient descent algorithms: Version 1.0.1

No description or website provided.

Bayesian inference for Gaussian mixture model with some novel algorithms

Misc Statistics and Machine Learning codes in R

KMeans for big data using preconditioning and sparsification, Matlab implementation. Aka k-means

Artificial intelligence/machine learning course at UCF in Spring 2020 (Fall 2019 and Spring 2019)

Implementations of machine learning algorithm by Python 3

Pipeline for fast building text classification TF-IDF + LogReg baselines.

Implementation of Machine Learning Algorithms

Cluster Algorithms from Scratch with Julia Lang. (K-Means and DBSCAN)

An introductory statistics course for social scientists, using Stata

PyTorch implementation of DeepGMR: Learning Latent Gaussian Mixture Models for Registration (ECCV 2020 spotlight)

Topic modelling on financial news with Natural Language Processing

Predicting the winner of 2019 cricket world cup using random forest algorithm

This 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.

By-hand code for models and algorithms. An update to the 'Miscellaneous-R-Code' repo.

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…

MATLAB/Octave library for stochastic optimization algorithms: Version 1.0.20

A sentiment classifier on mixed language (and mixed script) reviews in Tamil, Malayalam and English

🏆 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.

Machine learning, in numpy

Implementing Genetic Algorithm on K-Means and compare with K-Means++

AI Learning Hub for Machine Learning, Deep Learning, Computer Vision and Statistics

Gender recognition by voice and speech analysis

Heart Disease Analysis repository

Super fast simple k-means implementation for unidimiensional and multidimensional data.

Machine Learning models from scratch with a better visualisation

Gaussian Mixture Convolutional AutoEncoder applied to CT lung scans from the Kaggle Data Science Bowl 2017

Interactive Visual Machine Learning Demos.

Quick-Data-Science-Experiments

Probabilistic depth fusion based on Optimal Mixture of Gaussians for depth cameras

An unsupervised machine learning algorithm for the segmentation of spatial data sets.

Loan Application Data Analysis

No description or website provided.

A Python package to build predictive linear and logistic regression models focused on performance and interpretation

Multiple Regression Package for PHP

📈 Click-Through Rate Prediction using Logistic Regression and Tree Algorithms

Implementation of a Quantum inspired genetic algorithm proposed by A quantum-inspired genetic algorithm for k-means clustering paper.

机器学习-Coursera-吴恩达- python+Matlab代码实现

This VAD library can process audio in real-time utilizing GMM which helps identify presence of human speech in an audio sample that contains a mixture of speech and noise.

Sentiment Analysis & Topic Modeling with Amazon Reviews

Forecast stock prices using machine learning approach. A time series analysis. Employ the Use of Predictive Modeling in Machine Learning to Forecast Stock Return. Approach Used by Hedge Funds to Select Tradeable Stocks

This repo contains regression and classification projects. Examples: development of predictive models for comments on social media websites; building classifiers to predict outcomes in sports competitions; churn analysis; prediction of clicks on online ads; analysis of the opioids crisis and an analysis of retail store expansion strategies using…

Improved Fisher Vector Implementation- extracts Fisher Vector features from your data

Information Retrieval in High Dimensional Data (class deliverables)

Projects I completed as a part of Great Learning's PGP - Artificial Intelligence and Machine Learning

🍡 文本聚类 k-means算法及实战

Python implementation of Andrew Ng's ML course projects

Mobile(iOS) Text-to-Image search powered by multimodal semantic representation models(e.g., OpenAI's CLIP). Accepted at NAACL 2022.

Clustering 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.

The "breathing k-means" algorithm with datasets and example notebooks

中文文本分类实践，基于搜狗新闻语料库，采用传统机器学习方法以及预训练模型等方法

Machine learning algorithm such as KNN,Naive Bayes,Logistic Regression,SVM,Decision Trees,Random Forest,k means and Truncated SVD on amazon fine food review

My solution to TUM's Machine Learning MNIST challenge 2016-2017 [winner]

Final project of IBM's course https://www.coursera.org/learn/machine-learning-with-python on coursera

Built on data from Pluralsight's course API fetched results. Works with model trained with K-means unsupervised clustering algorithm.

This 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.