758 matching collectives

SOUL

About

Where Founders build their narrative.

Koncierge • E-commerce & Shopify Specialists

About

Sculpter votre e-commerce d'exception : stratégie, design & développement 💎

BEAURECIT

About

→ Book online : https://shorturl.at/gkcHv

Infodroid

About

Programmé pour l'innovation, conçu pour l'avenir informatique ! ©ChatGPT

Brunch ☕

About

Growth & Brand

Hyperstack

About

Data team as a Service

Blocs

About

Experts en construction d'espace Notion & knowledge management

Fonction Labs

About

Building the future of data for you

Brick Par Brick

About

Le collectif pour e-commerçant au service de votre croissance

Officehour

About

Collectif de 3 développeurs fullstack (IA, React, Go, PHP, Mobile)

Half Square

About

Bureau d'étude & Logiciel sur-mesure

OverSkill

About

OverSkill : le mouton à 12 pattes dont vous rêvez

Link

About

Collectif expert dans le design, le marketing, et le développement, nous sommes spécialisés dans les MVPs et les refontes Web/Mobile

Café Crème

About

Donnez vie à vos idées : Design & développement

Vendredi Society

About

Digital Design Studio :
Connecter les marques qui vont vite à des audiences en mouvement. La force créative d’équipes entièrement sur-mesure.

Yalla Cooperative

About

A flat-structure web design and development agency

Tekeo

About

Du concept au code, nous aidons les startups, TPE et PME à donner vie à leurs idées de produit

Qalitek

About

Une QA de qualité au service de la tech

BRED

Financial ServicesEnterprise


Machine Learning automation at BRED

Implementing big data pipelines and deploying machine learning models to predict and analyze customer behavior for a commercial bank.


Achievements:

• Big Data Pipeline Implementation: Setting up necessary infrastructures to collect and process data.

• Variable Processing and Aggregation: Using Spark and SQL queries to clean data and generate new features.

• Developing machine learning models in Python to automate money laundering detection in bank accounts.

• Deployment of Machine Learning Prediction App on AWS with Docker / Kubernetes.

• Implementing Large Language Models: Utilizing Hugging Face and Tensorflow for analyzing customer calls.

Impact :

• Improved Money Laundering Detection: Our model automates detection twice as effectively as competitors' previous models.

• Continuous Alert Filtering: Deploying the application on AWS ensures continuous filtering of irrelevant money laundering alerts, reducing costs and workload for operational teams.

• Enhanced Textual Call Analysis: Language models greatly improve the analysis of customer call records, facilitating the categorization of explanations for unusual transactions.

Members

Expertises

AWSPythonMachine Learning

From

Nov 2022 to Dec 2023