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aeon

A toolkit for conducting machine learning tasks with time series data

amit_refractorywear

amitkumargope

applieddeeplearning

This repository consists a set of Jupyter Notebooks with a different Deep Learning methods applied. Each notebook gives walkthrough from scratch to the end results visualization hierarchically. The Deep Learning methods include Multiperceptron layers, CNN, GAN, Autoencoders, Sequential and Non-Sequential deep learning models.

cfdpython

A sequence of Jupyter notebooks featuring the "12 Steps to Navier-Stokes" http://lorenabarba.com/

courses-introduction-to-python

Introduction to Python by Filip Schouwenaars

data-resources-for-materials-science

A list of databases, datasets and books/handbooks where you can find materials properties for machine learning applications.

deep-learning-roadmap

:satellite: All You Need to Know About Deep Learning - A kick-starter

deep-neural-networks-for-clogging-detection

Use Of Deep Neural Networks For Clogging Detection In The Submerged Entry Nozzle Of The Continuous Casting

easytsad

A framework for easy running and evaluating your TSAD algorithm.

keras-yolo3

Training and Detecting Objects with YOLO3

large-language-models

Large language Models (LLM)

mimad-gan

modern-time-series-forecasting-with-python

Modern Time Series Forecasting with Python, published by Packt

python-time-series-handbook

Notebooks for the course "Time series analysis with Python"

remote-jobs

A project for collecting remote jobs, updated daily 👩‍💻

short-term-energy-demand-forecasting

Forecasts next 24 hours of hourly energy demand with Keras, Prophet, and SARIMA (statsmodels)

sktime

A unified framework for machine learning with time series

tensorflow-certification-study-guide

Material and code samples used to help study for and pass the TensorFlow Developer Certification

the-art-of-command-line

Master the command line, in one page

units-learning

A unified time series model.

unsupervised_anomaly_detection

A Notebook where I implement differents anomaly detection algorithms on a simple exemple. The goal was just to understand how the different algorithms works and their differents caracteristics.