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jupyter notebook

big-test-pretrainedklaas-shuffle

Lecture note of Numerical Analysis and Practice

This project explores the use of big data analytics and machine learning techniques to predict the likelihood of ICU admission among COVID-19 patients. It includes data cleansing, exploratory analysis, classification models, and clustering, implemented using Python (Pandas, Scikit-learn, Imbalanced-learn) and PySpark for distributed processing.

Team project for the Master's course Data Storage and Preparation at the BUT FIT. The aim of the second part of the project was to analyze the selected dataset and modify it into a form suitable for mining algorithms. The dataset chosen for the preparation was All countries details.

Project for the Master's course Statistics and Probability at the BUT FIT. Bayesian estimation and regression, statistical methods, prediction, approximation. Created using Jupyter notebook.

Project for the Master's course Statistics and Probability at the BUT FIT. The project analyses the running times of six different algorithm configurations. A total of 200 independent runs were produced for each configuration, the logs of which are available in the logfiles.zip file. The project is created in Python Jupyter notebook.

nbgrader_setup.py helps you create jupyter nbgrader courses locally from the information in canvas courses. canvas2nbgrader.py will fetch student submissions from Canvas and package them appropriately to your jupyter nbgrader project. After you have graded the student material nbgrader2canvas.py is used to upload grades and feedback to Canvas again.

This template provides a structured way to set up a Python project using Jupyter Notebooks on macOS. It follows best practices, including virtual environment management, dependency tracking, and VSCode integration.

A collection of notebooks about maths, machine learning, and whatever...

Training project at DataQuest about historical numbers of helicopter assisted prison breaks in different countries.

A data analysis & data visualization tool to study bank statements

Example Jupyter Book site using GitLab Pages: https://paraskevasleivadaros.gitlab.io/jupyterbook

Jupyter Book is an open source project for building beautiful, publication-quality books and documents from computational material.

Training various machine learning models for NFLX stock price prediction with data collection, cleaning, and visualization tools.

This project focuses on extracting and visualizing stock data using Python libraries such as yfinance for historical stock prices and web scraping techniques to gather company revenue data. It provides a comprehensive analysis by plotting both stock prices and revenues over time for companies like Tesla and GameStop.

This project predicts house prices using machine learning models based on the King County House Sales dataset. It explores Simple Linear, Multiple Linear, Polynomial, and Ridge Regression models, comparing their performance in terms of accuracy. The best model identified is Polynomial Regression, achieving an R² score of 0.75.

Python para el procesamiento de señales.