780 Open source projects that are alternatives of or similar to Fuku Ml

Code for Tensorflow Machine Learning Cookbook

Python code for common Machine Learning Algorithms

Accompanying source code for Machine Learning with TensorFlow. Refer to the book for step-by-step explanations.

Estudo e implementação dos principais algoritmos de Machine Learning em Jupyter Notebooks.

An Interactive Approach to Understanding Deep Learning with Keras

100 Days of ML Coding

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

MATLAB/Octave library for stochastic optimization algorithms: Version 1.0.20

Matlab library for gradient descent algorithms: Version 1.0.1

Decision 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

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…

Practice and tutorial-style notebooks covering wide variety of machine learning techniques

My journey to learn and grow in the domain of Machine Learning and Artificial Intelligence by performing the #100DaysofMLCode Challenge.

General Assembly's 2015 Data Science course in Washington, DC

Machine Learning models from scratch with a better visualisation

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

Starter code of Prof. Andrew Ng's machine learning MOOC in R statistical language

🏭 JavaScript Machine Learning Toolkit

machine learning algorithm

numpy 实现的 周志华《机器学习》书中的算法及其他一些传统机器学习算法

simple tutorial on Machine Learning with Scikitlearn

Collection of stats, modeling, and data science tools in Python and R.

Code for Java Deep Learning Cookbook

🍊 📊 💡 Orange: Interactive data analysis

LIBSVM bindings for Julia

An introductory statistics course for social scientists, using Stata

Generalized Analog Regression Downscaling (GARD) code

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。

An Interactive Approach to Understanding Supervised Learning Algorithms

Misc Statistics and Machine Learning codes in R

dzetsaka : classification plugin for Qgis

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

Information Retrieval in High Dimensional Data (class deliverables)

Multiple Regression Package for PHP

D-Lab's 6 hour introduction to machine learning in R. Learn the fundamentals of machine learning, regression, and classification, using tidymodels in R.

A simple movie recommendation engine

Conceptual & empirical comparisons between decision forests & deep networks

Predicting Google’s stock price using regression

Project work and Assignments for Machine learning specialization course on Coursera by University of washington

Loan Application Data Analysis

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

ugtm: a Python package for Generative Topographic Mapping

Vectorized Machine Learning in Python 🐍 From Scratch

🏆 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.

Online machine learning methods

This repository contains all the programming exercises in Python for the Coursera course called "Machine Learning" by Adjunct Professor Andrew Ng at Stanford University.

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.

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

Interactive Visual Machine Learning Demos.

Minimalistic Multiple Layer Neural Network from Scratch in Python.

The main aim of this project is to tell that the certain project will be successful or it will fail by applying machine learning algorithm. In this , LOGISTIC REGRESSION is used to determine the success of the project by splitting the data into training and testing models and predicting a successful one.

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

Makes Interactive Chart Widget, Cleans raw data, Runs baseline models, Interactive hyperparameter tuning & tracking

机器学习-Coursera-吴恩达- python+Matlab代码实现

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

InstantDL: An easy and convenient deep learning pipeline for image segmentation and classification

Regression, Scrapers, and Visualization

Machine Learning Course @ Santa Clara University

Variational Bayes linear and logistic regression

Various methods for generating synthetic data for data science and ML