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How MLOps will streamline your AI projects?
When speaking of Artificial Intelligence, the efficiency and profitability of projects depend on the ability of companies to deploy reliable applications quickly and at low cost. To succeed, you need to organize and improve the processes for creating, implementing, and maintaining AI models with a diverse and sizable team.
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Don’t just build models, deploy them too!
You don’t know what “model deployment” means? Even when you try to understand what it means, you end up searching for the meaning of too many baffling tech words like “CI/CD”, “REST HTTPS API”, “Kubernetes clusters”, “WSGI servers”… and you feel overwhelmed or discouraged by this pile of new concepts?
Un-risk Model Deployment with Differential Privacy
As a general rule, all data ought to be treated as confidential by default. Machine learning models, if not properly designed, can inadvertently expose elements of the training set, which can have significant privacy implications. Differential privacy, a mathematical framework, enables data scientists to measure the privacy leakage of an algorithm. However, it is important to note that differential privacy necessitates a tradeoff between a model's privacy and its utility. In the context of deep learning there are available algorithms which achieve differential privacy. Various libraries exist, making it possible to attain differential privacy with minimal modifications to a model.
A Beginner's Guide to MLOps
MLOps is the combination of Machine Learning and Operations. Like DevOps for the software world, the concatenation of "ML" with the agile execution methodology "Ops", augurs a coming of age of Machine Learning.
L'industrialisation de l'IA & le concept de MLOps
Le MLOps apparaît comme une nécessité pour pallier les difficultés lors du passage à l’échelle de l’IA au sein des entreprises : la reproductibilité, le versionning, l'intégration continue... C’était l’objet de l’une des conférence sur l'industrialisation de l'intelligence artificielle dans le cadre de l'Enjeu Day Industrie & Services 2022. Vous n’aviez pas pu y assister ? Retrouvez le replay.
Implement PostgreSQL Pool connection in Rust
At Craft AI, we build a new product so data scientists can code and push, quickly and easily, in production, their machine learning algorithms. Our purpose is to make life easier for data scientists, for example, we handle data storage in a nice way so data scientists do not have to bother with saving and loading data from a database.
Les opportunités d’usage de l’IA dans le retail
L’intelligence artificielle connaît depuis quelques années un regain d'intérêt médiatique. L’IA, technologie d’utilité générale applicable dans l’ensemble des domaines de la société, laisse entrevoir des impacts économiques et sociaux considérables
Immersion dans la préhistoire grâce à l'IA
Pouvoir se promener dans une grotte habitée il y a plus de 500 000 ans, visualiser les restes d’une occupation humaine puis sortir dans la vallée qui la borde pour observer la faune et la flore de cette époque : voilà le rêve des archéologues du site de Tautavel, dans les Pyrénées-Orientales.
Cybersécurité : Astek et Craft AI s’associent
Astek et Craft AI, engagées dans un partenariat de codéveloppement de solutions de machine learning, présentent leur première réalisation dans le domaine de la cybersécurité. Les 2 entreprises ont codéveloppé un système d’authentification continue basé sur l’analyse comportementale des utilisateurs de systèmes informatiques.
Personalized virtual coach with Machine Learning
Imagine a fitness app where a virtual assistant helps users to reach their goals and to stay motivated. For the assistant to be engaging, it must give actionable and personalized advice, and adjust the plan to the actual progress of the user. In other words, a good coach must know its coachee.
Predictive UX boosts your website conversion rate
As many web-based marketplaces, banks rely on their website and mobile app to propose products like loans and insurances to the users. The conversion rate, that is to say the percentage of visitors that purchase a product, is often pretty low. The reasons are multiples: a great diversity of offers, non-targeted propositions, doubtful users… This article presents how Craft AI boost a website conversion rate by proposing adapted products to the users using predictive UX and hyper-personalized content.
Automated periodicity detection in time series
We recently presented a scientific paper during ECML PKDD Advanced Analytics and Learning on Temporal Data workshop part of the ECML-PKDD 2019 conference at Wurzburg, Germany.
How operationalizing AI improves online retailers
Online retail websites depend on their ability to understand their customer habits and wishes. These websites need to know which type of products interests which visitor and when they should make a suggestion.