M

machine learning

Practical tasks on Deep Learning (DL) and Neural Networks (NN). 🤖

Hybrid cloud-edge ML system for predictive rain control with automated retraining, monitoring, and Raspberry Pi hardware actuation.

Python software for identifying dynamical systems and hidden patterns from time series data

Découverte de ce monde (Data / ML) via un projet perso. Basés sur des relevés météo de différentes sources, avec des outils comme Pandas, Dask, Spark, Polars, ..., du ML et du DL. Une couche de visualisation via PowerBI.

$ mldev | is a data science experiment automation and reproducibility toolkit.

check our experiment templates: https://gitlab.com/mlrep

This repo will have all resources, labs, data which I use/d on Kaggle Network

IndyPy Talk 2023-02-14: Using AWS Artificial Intelligence services with Python https://www.meetup.com/indypy/events/289628031/

Python Panamá Meetup Vol 41 Usando Servicios Administrados de AI de AWS con Python y Boto3 https://www.meetup.com/python-panama/events/300787609/

Model_of_Virality is a machine learning and data-modelling initiative designed to analyse image-memes and identify the features that drive their online spread. Leveraging visual attributes (such as composition, subject matter and emotion) and sharing metrics, the system trains models to predict a meme’s likelihood of “going viral.” By combining statistical analysis with practical-engineering pipelines, the project provides both insight into what makes a meme successful and a reusable framework for meme virality prediction.

Source code for a kinetic theory inspired learning model for data-science applications. Manuscript: https://doi.org/10.1088/2632-2153/adf93a

A project that utilizes machine learning to predict shrimp growth to optimize the amount of feed used.

FakET: Simulating Cryo-Electron Tomograms with Neural Style Transfer

Instance Hardness analysis in Machine Learning

programas para medición de variables agro-hidrológicas. Datos obtenidos de esas mediciones y su correspondiente análisis.

Here’s the source code for my exploratory data analysis and model training for a movie recommendation system. The main model deployment code is in this repository.

Deployment Repo: (https://gitlab.com/aydie/ml-model-netflix-recommendation-system)

Website: aydie.in Contact: business@aydie.in

Resources for interns and new team members at Tangible AI