Python Helper library for Jupyter Notebooks

These are python notebooks accompanying Lessons available at GeostatisticsLessons.com

Convert Rmd (rmarkdown) to ipynb (Jupyter notebook)

Python notebooks for my graduate class on Detection, Estimation, and Learning. Intended for in-class demonstration. Notebooks illustrate a variety of concepts, from hypothesis testing to estimation to image denoising to Kalman filtering. Feel free to use or modify for your instruction or self-study.

🐸 Simple notebook to stream torrent files to Google Drive using Google Colab.

Pyspark Notebook With Docker

introduction to machine learning notebooks for physics education researchers

GitHub Action that runs flake8 code checks on Python code within Jupyter Notebooks

Exercises in Python notebook to implement the RSA encryption algorithm, and figure out if huge numbers are primes via Fermat test. Explanation provided via comments in Japanese.

A Beginner's Image Recognition Challenge in Python Tensorflow: Read README for more details on the project and on how to use notebook.

This repository contains the ipython notebook of covid19 study. This notebook was made possible in kaggle. Changes and improvements are always welcome.

This i python notebook contains the code for logistic regression with a neural network mindset.

Repository contains notebooks and datasets on no. of flights departures, passengers flew, flights crashed etc.

This notebook presents a Machine Learning Model Comparison for the Prediction of Rain in Australia

Collection of notes, papers, and python notebooks for ECE 5714 Robust Estimation and Filtering at Virginia Tech.

For the given ‘Iris’ dataset, create the Decision Tree classifier and visualize it graphically. The purpose is if we feed any new data to this classifier, it would be able to predict the right class accordingly.

In this notebook we analyze and classify news articles using machine learning techniques, including Logistic Regression, Naive Bayes, Support Vector Machines, and Random Forests. Explore text vectorization and NLP for accurate news categorization.

Python Notebooks

This Python notebook demonstrates the application of Support Vector Machines (SVM) for classification tasks on the MNIST dataset. The notebook covers data preprocessing, hyperparameter tuning, and dimensionality reduction using PCA.