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
Dieses Projekt ermöglicht es den Smartmeter der EVN (Netz Niederösterreich) über die Kundenschnittstelle auszulesen.

SmartMeterEVN Dieses Projekt ermöglicht es den Smartmeter der EVN (Netz Niederösterreich) über die Kundenschnittstelle auszulesen. Smart Meter werden

greenMike 43 Dec 04, 2022
Datetimes for Humans™

Maya: Datetimes for Humans™ Datetimes are very frustrating to work with in Python, especially when dealing with different locales on different systems

Timo Furrer 3.4k Dec 28, 2022
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
Pandas Machine Learning and Quant Finance Library Collection

Pandas Machine Learning and Quant Finance Library Collection

148 Dec 07, 2022
Cool Python features for machine learning that I used to be too afraid to use. Will be updated as I have more time / learn more.

python-is-cool A gentle guide to the Python features that I didn't know existed or was too afraid to use. This will be updated as I learn more and bec

Chip Huyen 3.3k Jan 05, 2023
XGBoost-Ray is a distributed backend for XGBoost, built on top of distributed computing framework Ray.

XGBoost-Ray is a distributed backend for XGBoost, built on top of distributed computing framework Ray.

92 Dec 14, 2022
Stacked Generalization (Ensemble Learning)

Stacking (stacked generalization) Overview ikki407/stacking - Simple and useful stacking library, written in Python. User can use models of scikit-lea

Ikki Tanaka 192 Dec 23, 2022
A python library for easy manipulation and forecasting of time series.

Time Series Made Easy in Python darts is a python library for easy manipulation and forecasting of time series. It contains a variety of models, from

Unit8 5.2k Jan 04, 2023
Kaggle Competition using 15 numerical predictors to predict a continuous outcome.

Kaggle-Comp.-Data-Mining Kaggle Competition using 15 numerical predictors to predict a continuous outcome as part of a final project for a stats data

moisey alaev 1 Dec 28, 2021
Visualize classified time series data with interactive Sankey plots in Google Earth Engine

sankee Visualize changes in classified time series data with interactive Sankey plots in Google Earth Engine Contents Description Installation Using P

Aaron Zuspan 76 Dec 15, 2022
Xeasy-ml is a packaged machine learning framework.

xeasy-ml 1. What is xeasy-ml Xeasy-ml is a packaged machine learning framework. It allows a beginner to quickly build a machine learning model and use

9 Mar 14, 2022
A framework for building (and incrementally growing) graph-based data structures used in hierarchical or DAG-structured clustering and nearest neighbor search

A framework for building (and incrementally growing) graph-based data structures used in hierarchical or DAG-structured clustering and nearest neighbor search

Nicholas Monath 31 Nov 03, 2022
TorchDrug is a PyTorch-based machine learning toolbox designed for drug discovery

A powerful and flexible machine learning platform for drug discovery

MilaGraph 1.1k Jan 08, 2023
Time series changepoint detection

changepy Changepoint detection in time series in pure python Install pip install changepy Examples from changepy import pelt from cha

Rui Gil 92 Nov 08, 2022
A Python implementation of the Robotics Toolbox for MATLAB

Robotics Toolbox for Python A Python implementation of the Robotics Toolbox for MATLAB® GitHub repository Documentation Wiki (examples and details) Sy

Peter Corke 1.2k Jan 07, 2023
All-in-one web-based development environment for machine learning

All-in-one web-based development environment for machine learning Getting Started • Features & Screenshots • Support • Report a Bug • FAQ • Known Issu

3 Feb 03, 2021
Hypernets: A General Automated Machine Learning framework to simplify the development of End-to-end AutoML toolkits in specific domains.

A General Automated Machine Learning framework to simplify the development of End-to-end AutoML toolkits in specific domains.

DataCanvas 216 Dec 23, 2022
A collection of video resources for machine learning

Machine Learning Videos This is a collection of recorded talks at machine learning conferences, workshops, seminars, summer schools, and miscellaneous

Dustin Tran 1.5k Dec 29, 2022
Machine Learning Model to predict the payment date of an invoice when it gets created in the system.

Payment-Date-Prediction Machine Learning Model to predict the payment date of an invoice when it gets created in the system.

15 Sep 09, 2022
Predicting India’s COVID-19 Third Wave with LSTM

Predicting India’s COVID-19 Third Wave with LSTM Complete project of predicting new COVID-19 cases in the next 90 days with LSTM India is seeing a ste

Samrat Dutta 4 Jan 27, 2022