aligeekk's Stars
trekhleb/homemade-machine-learning
🤖 Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained
ujjwalkarn/Machine-Learning-Tutorials
machine learning and deep learning tutorials, articles and other resources
stefan-jansen/machine-learning-for-trading
Code for Machine Learning for Algorithmic Trading, 2nd edition.
rasbt/python-machine-learning-book
The "Python Machine Learning (1st edition)" book code repository and info resource
RedditSota/state-of-the-art-result-for-machine-learning-problems
This repository provides state of the art (SoTA) results for all machine learning problems. We do our best to keep this repository up to date. If you do find a problem's SoTA result is out of date or missing, please raise this as an issue or submit Google form (with this information: research paper name, dataset, metric, source code and year). We will fix it immediately.
ljpzzz/machinelearning
My blogs and code for machine learning. http://cnblogs.com/pinard
rasbt/python-machine-learning-book-2nd-edition
The "Python Machine Learning (2nd edition)" book code repository and info resource
nfmcclure/tensorflow_cookbook
Code for Tensorflow Machine Learning Cookbook
dformoso/machine-learning-mindmap
A mindmap summarising Machine Learning concepts, from Data Analysis to Deep Learning.
rhiever/Data-Analysis-and-Machine-Learning-Projects
Repository of teaching materials, code, and data for my data analysis and machine learning projects.
susanli2016/Machine-Learning-with-Python
Python code for common Machine Learning Algorithms
zotroneneis/machine_learning_basics
Plain python implementations of basic machine learning algorithms
tirthajyoti/Machine-Learning-with-Python
Practice and tutorial-style notebooks covering wide variety of machine learning techniques
dipanjanS/practical-machine-learning-with-python
Master the essential skills needed to recognize and solve complex real-world problems with Machine Learning and Deep Learning by leveraging the highly popular Python Machine Learning Eco-system.
kk7nc/Text_Classification
Text Classification Algorithms: A Survey
tdpetrou/Machine-Learning-Books-With-Python
Chapter by Chapter notes, exercises and code for a variety of machine learning books using Python
JWarmenhoven/Coursera-Machine-Learning
Coursera Machine Learning - Python code
mbeyeler/opencv-machine-learning
M. Beyeler (2017). Machine Learning for OpenCV: Intelligent image processing with Python. Packt Publishing Ltd., ISBN 978-178398028-4.
WillKoehrsen/Machine-Learning-Projects
Machine Learning Experiments and Work
diefimov/MTH594_MachineLearning
The materials for the course MTH 594 Advanced data mining: theory and applications (Dmitry Efimov, American University of Sharjah)
PacktPublishing/Python-Machine-Learning-Blueprints
Code repository for Python Machine Learning Blueprints, published by Packt
jmartinezheras/2018-MachineLearning-Lectures-ESA
Machine Learning Lectures at the European Space Agency (ESA) in 2018
brinkar/real-world-machine-learning
Code accompanying the Real-World Machine Learning book
jmportilla/Udemy---Machine-Learning
Notebooks for Course
FlorianMuellerklein/Machine-Learning
Machine learning library written in readable python code
lucasayres/url-feature-extractor
Extracting features from URLs to build a data set for machine learning. The purpose is to find a machine learning model to predict phishing URLs, which are targeted to the Brazilian population.
diegoocampoh/MachineLearningPhishing
This project will determine which of the five supervised classification machine learning algorithms performs best in detecting phishy emails
srikanthiremath/Phishing-Detector-using-LR
Problem Statement The purpose of the project is to use one or more of the classification algorithms to train a model on the Phishing website dataset. You are provided with the following resources that can be used as inputs for your model: 1. A collection of website URLs for 11000+ websites. Each sample has 30 website parameters and a class label identifying it as a phishing website or not (1 or -1). 2. Code template containing these code blocks: a. Import modules (Part 1) b. Load data function + input/output field descriptions You are expected to write the code for a binary classification model (phishing website or not) using Python Scikit-Learn that trains on the data and calculates the accuracy score on the test data.
amoldy/ML.PhishingEmailDetection
reuleam/Phishing-Email-Project-2019
Phishing email project for Software Engineering 2019