Advanced Python Libraries for Data Science
Explore advanced Python libraries for data science, focusing on scikit-learn, TensorFlow, and PyTorch Geometric. Learn implementation, methodologies, and practical applications through code exercises.
Building a Fraud Detection Model with Feature Stores - Includes Shopify Case Study
Develop a real-time fraud detection system using ML data pipeline tools. Learn to build, deploy, and serve data pipelines with Feast and Tecton. Explore architectural patterns and model stages.
Introduction to Data Analysis Using Pandas
Learn to effectively analyze data using pandas in Python. Master data manipulation, aggregation, and visualization techniques for extracting valuable insights from tabular datasets.
Delta Live Tables: Building Reliable Data Pipelines with Databricks
Simplify ETL development with declarative pipelines, automatic testing, and deep visibility for reliable batch and streaming data on Databricks Lakehouse Platform.
Технология Использования Съемки в Режиме Кинематика (ППК) - Часть I
Изучите технологию съемки в режиме кинематика (ППК) для геодезических работ. Освойте основы и принципы применения этого метода в полевых условиях.
Обработка данных 3
Освойте методы обработки данных для повышения эффективности в геологии и нефтегазовых технологиях. Развивайте навыки анализа и управления информацией.
How to Rangify Your Code - C++ on Sea 2022
Learn to apply C++20 ranges to real-world code examples, using standard library and range-v3 library. Explore techniques for refactoring existing algorithms and thinking in terms of ranges.
Powering Applications with High-Volume Data and APIs in Kubernetes
Discover how Kubernetes SIG Apps has evolved to support diverse workloads, from stateless to stateful applications, while exploring its milestones, sub-projects, and future developments in cloud-native application management.
Orchestrating Quasi-Real Time Data Processing in the Computing Farm of the ATLAS Experiment at CERN
Discover how CERN's ATLAS experiment leverages Kubernetes to orchestrate massive data processing, managing 25,000 pods across 2,500 nodes for real-time physics event filtering at 5 TB/s.
Elevating Kubeflow Spark Operator's Future: Best Practices and Enhancements
Discover advanced techniques for deploying Apache Spark on Kubernetes using Kubeflow Spark Operator, covering scaling strategies, multi-tenancy management, security best practices, and efficient upgrade procedures.
Bloomberg's Journey to Manage Multi-Cluster Training Applications with Karmada
Discover how Bloomberg leverages Karmada to manage multi-cluster GPU workloads, optimize resource utilization, and streamline AI model training across data centers with intelligent scheduling and high availability.
Leveraging Pre-trained Vision Foundation Models for Geophysical Data Processing and Interpretation
Discover how to adapt computer vision foundation models for geoscience applications, focusing on efficient processing and interpretation of geophysical data like seismic and lunar imagery.
Nextflow and Julia for Scalable Computation
Discover powerful computational tools for scalable data processing, combining Nextflow's workflow management capabilities with Julia's high-performance computing features.
Unlocking Advanced Processing Capabilities with OpenTelemetry
Discover how to optimize OpenTelemetry's processing capabilities for effective data transformation, filtering, sampling, and routing in distributed systems while managing costs and overhead.
Turn the Volume Down on Noisy Neighbors - Intelligent Log Routing in Multi-tenant Kubernetes
Discover how to effectively manage multi-tenant logging in Kubernetes using the Telemetry Controller, enabling intelligent routing and tenant isolation for improved log management and filtering.
Breaking the 1.5MB Barrier: Running Large Metaflow Flows with Argo for AI/ML Workloads
Discover how to overcome Argo's 1.5MB size limitation for large-scale AI/ML workflows using Aurora Postgres RDS and EKS, enabling efficient management of extensive batch processes and data preparation tasks.
Observability Data Volumes and Strategies for Managing System Growth
Explore strategies for managing growing observability data volumes, from historical growth patterns to current solutions and future possibilities in data processing and storage optimization.
Multitenancy and Fairness at Scale with Kueue - A Kubernetes Batch System Case Study
Explore how Kueue implements job queueing and resource sharing in Kubernetes, featuring fair sharing mechanisms, quota management, and performance optimizations for large-scale ML platforms.
Catching Waves with Time-Series Data - Best Practices for Storage and Analysis
Dive into time-series data management through a surfer's journey, exploring efficient storage, querying, aggregation, and API implementation for real-world applications in IoT and finance.
Распределённое хранение и обработка больших данных
Dive into распределённое хранение и обработку больших данных с открытым ПО Яндекса, изучая методы отображения изменяемых таблиц на неизменяемые фрагменты для эффективной обработки данных.
Apache Gluten - Boosting Apache Spark Performance with Native Engines
Discover how Apache Gluten enhances Spark performance through native engine integration, optimizing data processing and analysis capabilities for improved efficiency.