Jupyter Notebooks from the old UnsupervisedLearning.com (RIP) machine learning and statistics blog
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Updated
Apr 25, 2023 - Jupyter Notebook
The Jupyter Notebook, previously known as the IPython Notebook, is a language-agnostic HTML notebook application for Project Jupyter. Jupyter notebooks are documents that allow for creating and sharing live code, equations, visualizations, and narrative text together. People use them for data cleaning and transformation, numerical simulation, statistical modeling, data visualization, machine learning, and much more.
Jupyter Notebooks from the old UnsupervisedLearning.com (RIP) machine learning and statistics blog
A repository for sharing ipynb's of my experiments with ML. Some notebooks are 'old' by now and might no longer work 'out of the box'.
Python crawling tutorial
A jupyter notebook server via HEROKU web without Password.
Movie Recommendation System based on machine learning concepts
Rock Paper Scissors with OpenCV and Neural Networks
Parch and Posey database was used to explore different functional aspects of SQL from basic to advanced.
Welcome to the Python-Starter-Codes repository! Here, you'll find a comprehensive set of Python starter code that's perfect for beginners who are just starting to learn the language. Whether you're a complete novice or just looking to brush up on your skills, this repository has everything you need to get started with Python.
🗂 markdown tool to create table of content from jupyter notebooks
Interactive Machine Learning Examples
This repository contains code archives for Diabetes Prediction with Machine Learning
A predictive model for Order Cancellation among customers to try to predict suspicious bookings in the hotel industry
Basic pattern recognition algorithms implemented in Python
Hangman Game using Python
A Digital Twin prototype for aircraft engine health management in order to identify possible faults and to predict its remaining useful life
Developed a personalized game recommendation system combining K-Means clustering and Nearest Neighbors algorithms to suggest games based on user preferences and game attributes. The system mitigates decision paralysis by offering tailored recommendations using game features like price, platform, genres, and release year. We implemented content-base
Created by Fernando Pérez, Brian Granger, and Min Ragan-Kelley
Released December 2011
Latest release about 1 month ago