Inria establishes a foundation to secure funding and support for the scikit-learn open-source machine learning library, enabling sustainable growth and development.
A technical explanation of Variational Autoencoders (VAEs), covering their theory, latent space, and how they generate new data.
Explains four levels of customer targeting, from no segmentation to advanced recommendation systems, and their business applications.
Explains how Taboola built a unified neural network model to predict CTR and estimate prediction uncertainty for recommender systems.
A report on recent scikit-learn sprints in Austin and Paris, highlighting new features, bug fixes, and progress toward the 0.20 release.
Explores how uncertainty estimation in deep neural networks can be used for model interpretation, debugging, and improving reliability in high-risk applications.
A review and tips for Georgia Tech's OMSCS CS7642 Reinforcement Learning course, covering workload, projects, and key learnings.
A developer recounts the process of reviving a deprecated open-source Python library for parsing recipe ingredients, detailing the challenges of legacy code.
Explains the attention mechanism in deep learning, its motivation from human perception, and its role in improving seq2seq models like Transformers.
A data science leader shares challenges of scaling a data science team at Lazada, focusing on balancing business input with ML automation.
Highlights from a deep learning conference covering optimization algorithms' impact on generalization and human-in-the-loop efficiency.
A practical guide to implementing a hyperparameter tuning script for machine learning models, based on real-world experience from Taboola's engineering team.
A tutorial on implementing a binary classification machine learning model using ML.NET in .NET Core to predict Titanic passenger survival.
A data science VP shares how Lazada uses machine learning for e-commerce, including automated review classification and product ranking.
A comprehensive overview of policy gradient algorithms in reinforcement learning, covering key concepts, notations, and various methods.
Exploring machine learning-driven bundling with Guess.js to optimize JavaScript chunk loading and improve SPA performance.
An introductory guide to Reinforcement Learning (RL), covering key concepts, algorithms like SARSA and Q-learning, and its role in AI breakthroughs.
Explores the Multi-Armed Bandit problem, a classic dilemma balancing exploration and exploitation in decision-making algorithms.
A web developer shares their journey learning machine learning, applying JavaScript skills to a new domain and rediscovering math.
A personal reflection on the author's achievements in 2017, including travel, starting a club, and fitness goals, with a positive outlook for 2018.
