Workshop: Building Recommender Systems w/ Apache Spark 2.x
Apache Spark has become one of the must-know big data technologies due to its speed, ease of use, and versatility. Spark can be used for performing data analysis and building big-data applications. Increasingly, companies are leveraging Apache Spark to build intelligent applications that use Machine Learning techniques. This workshop will start with covering the major features in Spark 2.x and then focus on building a recommendation system using Spark MLlib library. It will include focused and interactive hands-on exercises.
Signup for a free Databricks Community Edition account - https://community.cloud.
Tutorial materials can be found at - https://sites.google.com/view/apache-spark-workshop/
Here is what you can expect to learn from this tutorial:
- Spark architecture and execution model
- Structured data processing with Spark SQL, DataFrames, and Datasets
- Streaming processing with Structure Streaming
- Major concepts and utilities in Spark ML library for building intelligent applications
- Build a recommender system using Spark ML library
Other Workshops:
Tracks
Monday, 5 November
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Microservices / Serverless Patterns & Practices
Evolving, observing, persisting, and building modern microservices
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Practices of DevOps & Lean Thinking
Practical approaches using DevOps & Lean Thinking
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JavaScript & Web Tech
Beyond JavaScript in the Browser. Exploring WebAssembly, Electron, & Modern Frameworks
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Modern CS in the Real World
Thoughts pushing software forward, including consensus, CRDT's, formal methods, & probabilistic programming
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Modern Operating Systems
Applied, practical, & real-world deep-dive into industry adoption of OS, containers and virtualization, including Linux on Windows, LinuxKit, and Unikernels
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Optimizing You: Human Skills for Individuals
Better teams start with a better self. Learn practical skills for IC
Tuesday, 6 November
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Architectures You've Always Wondered About
Next-gen architectures from the most admired companies in software, such as Netflix, Google, Facebook, Twitter, & more
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21st Century Languages
Lessons learned from languages like Rust, Go-lang, Swift, Kotlin, and more.
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Emerging Trends in Data Engineering
Showcasing DataEng tech and highlighting the strengths of each in real-world applications.
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Bare Knuckle Performance
Killing latency and getting the most out of your hardware
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Socially Conscious Software
Building socially responsible software that protects users privacy & safety
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Delivering on the Promise of Containers
Runtime containers, libraries, and services that power microservices
Wednesday, 7 November
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Applied AI & Machine Learning
Applied machine learning lessons for SWEs, including tech around TensorFlow, TPUs, Keras, PyTorch, & more
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Production Readiness: Building Resilient Systems
More than just building software, building deployable production ready software
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Developer Experience: Level up your Engineering Effectiveness
Improving the end to end developer experience - design, dev, test, deploy, operate/understand.
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Security: Lessons Attacking & Defending
Security from the defender's AND the attacker's point of view
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Future of Human Computer Interaction
IoT, voice, mobile: Interfaces pushing the boundary of what we consider to be the interface
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Enterprise Languages
Workhorse languages found in modern enterprises. Expect Java, .NET, & Node in this track
