
Explore high-throughput data processing with Akka Streams, comparing it to Akka Actors. Learn best practices, optimization techniques, and when to switch to Streams for improved performance in large-scale data transfer systems.

Explore 2D data visualization in Scala with Doodle. Learn to create flexible, customizable graphs for browser, desktop, and file output using functional programming techniques.

Learn to analyze large datasets of compromised passwords using Apache Spark, exploring data processing techniques and security implications in this Scala Days conference talk.

Explore Apache Spark's Datasets and functional programming techniques for efficient data processing, with insights on maintaining code readability and performance optimization.

Learn patterns for streaming telemetry using Akka Streams, including error handling, grouping, filtering, rate limiting, and concurrency, with practical examples and best practices.

Explore an expressive Kafka Streams API tailored for Scala developers, enhancing stream processing capabilities and improving code readability in distributed systems.

Explore event-driven programming, micro-services, and fast data concepts for building scalable systems with feedback control and promise theory.

Explore functional programming techniques in Apache Spark Datasets with Holden Karau, focusing on maintaining enjoyment while leveraging powerful data processing capabilities.

Learn to analyze compromised passwords using Apache Spark, exploring data processing techniques and security implications in this Scala Days conference talk.

Explore the transformation to real-time enterprise systems with insights on challenges, solutions, and the future of data-driven businesses in this keynote by Neha Narkhede.

Explore advanced Akka Streams features, including simplified demos, source queues, promises, and testing techniques. Learn about branching, merging, and practical applications like word shuffling and text processing.

Explore the journey of unification from Apache Spark to MLflow, highlighting key developments and innovations in big data processing and machine learning workflows.

Explore interactive computing using Jupyter and Almond for Scala development. Learn to create dynamic, shareable notebooks for data analysis, visualization, and machine learning projects.

Explore advanced metaprogramming techniques in Dotty, the next-generation Scala compiler, to enhance code generation and manipulation capabilities for more powerful and flexible programming.

Explore asynchronous streams in Scala using for-comprehensions, scala-async, and macro-based implementations, with insights on Reactive Streams and Project Loom.

Explore functional streams, from basic pure programs to effects and concurrency. Build mental models for stream evaluation and learn to reason through complex code using practical examples and frameworks.

Explore ducktape, a macro-based library for Scala 3 that streamlines JSON handling, reduces boilerplate, and enhances productivity in common development scenarios.

Explore Magnum, a new Scala 3 database client combining macros and structural types for typesafe, IDE-refactorable SQL interfaces across JDBC-supported databases.

Explore Gallia, a schema-aware Scala library for practical data transformation. Learn its benefits, usage, and comparison with alternatives like Pandas and Apache Spark through live coding demonstrations.

Explore building billion-node graphs for machine learning, covering data ingestion, graph management, and algorithm execution at scale. Learn about challenges and solutions in handling massive datasets for GraphML research.

Explore how programmers can aid epidemiologists by gathering and analyzing COVID-19 data using Ruby, web tools, and expressive code to make complex information understandable.