M

machine learning

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

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

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

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.

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

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

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

This projects implements neural-network controllers for two agent-based models: (i) a predator-prey model and (ii) a metabolic network model.

This project aimed at exploring the potential of learning sketching matrices used with HOSVD for Tucker Decomposition of tensors.

Predicting mobile/digital banking patterns and adoption across Southeast Asian countries using World Bank data

Big Data) Predicting first day market capitalization using Nasdaq reference grade stock data for US tech startups