Coursera Machine Learning - Python code

Overview

Coursera Machine Learning

This repository contains python implementations of certain exercises from the course by Andrew Ng.

For a number of assignments in the course you are instructed to create complete, stand-alone Octave/MATLAB implementations of certain algorithms (Linear and Logistic Regression for example). The rest of the assignments depend on additional code provided by the course authors. For most of the code in this repository I have instead used existing Python implementations like Scikit-learn.

Exercise 1 - Linear Regression
Exercise 2 - Logistic Regression
Exercise 3 - Multi-class Classification and Neural Networks
Exercise 4 - Neural Networks Learning
Exercise 5 - Regularized Linear Regression and Bias v.s. Variance
Exercise 6 - Support Vector Machines
Exercise 7 - K-means Clustering and Principal Component Analysis
Exercise 8 - Anomaly Detection and Recommender Systems

References:

https://www.coursera.org/learn/machine-learning/home/welcome

Owner
Jordi Warmenhoven
Data Visualization, Probabilistic Programming and Statistics Enthusiast | Fairly Bayesian | Mostly Python | Always curious
Jordi Warmenhoven
Tools for mathematical optimization region

Tools for mathematical optimization region

林景 15 Nov 30, 2022
Confidence intervals for scikit-learn forest algorithms

forest-confidence-interval: Confidence intervals for Forest algorithms Forest algorithms are powerful ensemble methods for classification and regressi

272 Dec 01, 2022
Python package for stacking (machine learning technique)

vecstack Python package for stacking (stacked generalization) featuring lightweight functional API and fully compatible scikit-learn API Convenient wa

Igor Ivanov 671 Dec 25, 2022
Send rockets to Mars with artificial intelligence(Genetic algorithm) in python.

Send Rockets To Mars With AI Send rockets to Mars with artificial intelligence(Genetic algorithm) in python. Tools Python 3 EasyDraw How to Play Insta

Mohammad Dori 3 Jul 15, 2022
Coursera Machine Learning - Python code

Coursera Machine Learning This repository contains python implementations of certain exercises from the course by Andrew Ng. For a number of assignmen

Jordi Warmenhoven 859 Dec 10, 2022
Credit Card Fraud Detection, used the credit card fraud dataset from Kaggle

Credit Card Fraud Detection, used the credit card fraud dataset from Kaggle

Sean Zahller 1 Feb 04, 2022
A collection of Scikit-Learn compatible time series transformers and tools.

tsfeast A collection of Scikit-Learn compatible time series transformers and tools. Installation Create a virtual environment and install: From PyPi p

Chris Santiago 0 Mar 30, 2022
SynapseML - an open source library to simplify the creation of scalable machine learning pipelines

Synapse Machine Learning SynapseML (previously MMLSpark) is an open source library to simplify the creation of scalable machine learning pipelines. Sy

Microsoft 3.9k Dec 30, 2022
Lightning ⚡️ fast forecasting with statistical and econometric models.

Nixtla Statistical ⚡️ Forecast Lightning fast forecasting with statistical and econometric models StatsForecast offers a collection of widely used uni

Nixtla 2.1k Dec 29, 2022
Laporan Proyek Machine Learning - Azhar Rizki Zulma

Laporan Proyek Machine Learning - Azhar Rizki Zulma Project Overview Domain proyek yang dipilih dalam proyek machine learning ini adalah mengenai hibu

Azhar Rizki Zulma 6 Mar 12, 2022
fMRIprep Pipeline To Machine Learning

fMRIprep Pipeline To Machine Learning(Demo) 所有配置均在config.py文件下定义 前置环境(lilab) 各个节点均安装docker,并有fmripre的镜像 可以使用conda中的base环境(相应的第三份包之后更新) 1. fmriprep scr

Alien 3 Mar 08, 2022
Relevance Vector Machine implementation using the scikit-learn API.

scikit-rvm scikit-rvm is a Python module implementing the Relevance Vector Machine (RVM) machine learning technique using the scikit-learn API. Quicks

James Ritchie 204 Nov 18, 2022
Bodywork deploys machine learning projects developed in Python, to Kubernetes.

Bodywork deploys machine learning projects developed in Python, to Kubernetes. It helps you to: serve models as microservices execute batch jobs run r

Bodywork Machine Learning 409 Jan 01, 2023
Painless Machine Learning for python based on scikit-learn

PlainML Painless Machine Learning Library for python based on scikit-learn. Install pip install plainml Example from plainml import KnnModel, load_ir

1 Aug 06, 2022
Lightweight Machine Learning Experiment Logging 📖

Simple logging of statistics, model checkpoints, plots and other objects for your Machine Learning Experiments (MLE). Furthermore, the MLELogger comes with smooth multi-seed result aggregation and co

Robert Lange 65 Dec 08, 2022
Toolss - Automatic installer of hacking tools (ONLY FOR TERMUKS!)

Tools Автоматический установщик хакерских утилит (ТОЛЬКО ДЛЯ ТЕРМУКС!) Оригиналь

14 Jan 05, 2023
AutoTabular automates machine learning tasks enabling you to easily achieve strong predictive performance in your applications.

AutoTabular AutoTabular automates machine learning tasks enabling you to easily achieve strong predictive performance in your applications. With just

wenqi 2 Jun 26, 2022
Machine Learning Algorithms ( Desion Tree, XG Boost, Random Forest )

implementation of machine learning Algorithms such as decision tree and random forest and xgboost on darasets then compare results for each and implement ant colony and genetic algorithms on tsp map,

Mohamadreza Rezaei 1 Jan 19, 2022
This is an implementation of the proximal policy optimization algorithm for the C++ API of Pytorch

This is an implementation of the proximal policy optimization algorithm for the C++ API of Pytorch. It uses a simple TestEnvironment to test the algorithm

Martin Huber 59 Dec 09, 2022
Fourier-Bayesian estimation of stochastic volatility models

fourier-bayesian-sv-estimation Fourier-Bayesian estimation of stochastic volatility models Code used to run the numerical examples of "Bayesian Approa

15 Jun 20, 2022