Stepping into Data Science - Predictive Analytics
Explore data science processes, feature engineering, and predictive analytics using Python. Learn to create training and predictive experiments with practical examples and machine learning techniques.
Building a Cloud Native Feature Store with Feast on Kubeflow
Explore how Feast, an open-source feature store, solves key challenges in machine learning feature engineering, from data processing to production deployment, within a cloud-native Kubeflow environment.
Cloud Native Machine Learning Systems at Day Two and Beyond
Explore challenges and solutions for cloud-native machine learning systems, covering reproducibility, monitoring, and DevOps tools for mature ML implementations in production environments.
Machine Learning with Scala on Spark
Explore machine learning with Spark and Scala, comparing frameworks, discussing advantages, and addressing challenges in data science. Gain insights into Spark.ml's capabilities and potential for predictive modeling.
Doubt Truth to Be a Liar - Non Triviality of Type Safety for Machine Learning
Explore type-safe feature engineering in Scala for machine learning, covering Shapeless, macros, and quasiquotes to enhance ML framework design and model accuracy.
Visual Feature Engineering for Machine Learning with React
Explore visual feature engineering for machine learning using React and TensorFlow.js to predict soccer match outcomes, with real-time model visualization and training insights.
Not a Magic - What to Expect from Machine Learning Projects
Practical insights on implementing machine learning projects, covering data handling, algorithm selection, training, evaluation, and deployment challenges in organizational settings.
Boosting Data Science Routines with DataArt's AutoML Platform
Discover how DataArt's DS/ML Platform automates data science workflows through feature engineering, model selection, and deployment - suitable for both expert and citizen data scientists.
Container Tracking and Demand Forecasting for Bosch Tools Supply Chain Operations
Discover how BOSCH Power Tools leverages neural forecasting models in AWS cloud to optimize demand forecasting, reduce inventory costs, and enhance supply chain stability for millions of product time series.
A Type System for Feature Engineering in Machine Learning
Explore a dependent type system for feature engineering, enhancing machine learning model inputs through advanced data operations and compiler techniques.
Designing a Real-Time Model to Prevent Fake Account Sign-Up
Develop a real-time machine learning service to prevent fake account sign-ups. Learn about statistical challenges, computational scaling, and deployment pitfalls in low-latency ML inference.
Effect of Feature Engineering in Logistic Regression
Explore feature engineering's impact on logistic regression, covering sigmoid curves, non-monotonic relationships, and sinusoidal patterns.
Geometry of Regression Model and Feature Engineering
Explore regression model geometry and feature engineering techniques to enhance data analysis and model performance.
Building a Python-Centric Feature Platform to Power Production AI Applications
Explore Tecton's journey in developing a Python-based platform for powering large-scale real-time AI applications. Learn about reliable solutions for productionizing AI using only Python skills.
Fabricator - Streamlining Declarative Feature Engineering at DoorDash
Découvrez comment DoorDash a développé Fabricator, un framework complet pour rationaliser l'ingénierie des caractéristiques déclaratives, orchestrant efficacement 1400 tâches quotidiennes et gérant 2,2 billions de valeurs.
Predictive ML - How Unilever is Improving its Forecasting
Unilever's reusable predictive framework improves forecasting processes using ML models, enhancing manual predictions and filling gaps for various business metrics at different granularity levels.
Leveraging Graphs for AI
Explore graph theory's role in AI, from data structures to machine learning, with practical examples and applications in analytics, algorithms, and neural networks.
Building an Open-Source Online Learn-to-Rank Engine - Haystack EU 2022
Explore Metarank, an open-source personalization service for learn-to-rank tasks. Discover how it simplifies data engineering challenges and improves search relevancy through visitor behavior analysis.
Effective Relevancy Change Management in Search Systems
Explore effective search relevancy change management techniques for continuous improvement in search systems and feature engineering.
Data Preprocessing and Feature Engineering for Machine Learning
Master data preprocessing and feature engineering techniques for effective machine learning. Explore imputation, encoding, transformations, and more to maximize value from your data and improve model performance.
Building a Unified Feature Platform with DuckDB and Arrow
Explore ML feature platform development using DuckDB and Arrow. Learn scaling strategies, DuckDB extension implementation, DeltaLake interoperability, and performance comparison with Spark.