Conference: Jun 26-28, 2017
Workshops: Jun 29-30, 2017
Presentation: Machine Learning from Theory to Practice
Abstract
With recent advances in computational power, machine learning is positioned to change the way we interact with the world around us. Likewise, a surge of well-maintained machine learning libraries has made it possible for engineers to use machine learning models with minimal background. However, many find that using machine learning responsibly in your company can be harder than it seems. Here, we will discuss some of the challenges that can arise when working with data.
Similar Talks
Tracks
Monday, 26 June
-
Microservices: Patterns & Practices
Practical experiences and lessons with Microservices.
-
Java - Propelling the Ecosystem Forward
Lessons from Java 8, prepping for Java 9, and looking ahead at Java 10. Innovators in Java.
-
High Velocity Dev Teams
Working Smarter as a team. Improving value delivery of engineers. Lean and Agile principles.
-
Modern Browser-Based Apps
Reactive, cross platform, progressive - webapp tech today.
-
Innovations in Fintech
Technology, tools and techniques supporting modern financial services.
Tuesday, 27 June
-
Architectures You've Always Wondered About
Case studies from the most relevant names in software.
-
Developer Experience: Level up Your Engineering Effectiveness
Trends, tools and projects that we're using to maximally empower your developers.
-
Chaos & Resilience
Failures, edge cases and how we're embracing them.
-
Stream Processing at Large
Rapidly moving data at scale.
-
Building Security Infrastructure
How our industry is being attacked and what you can do about it.
Wednesday, 28 June
-
Next Gen APIs: Designs, Protocols, and Evolution
Practical deep-dives into public and internal API design, tooling and techniques for evolving them, and binary and graph-based protocols.
-
Immutable Infrastructures: Orchestration, Serverless, and More
What's next in infrastructure. How cloud function like lambda are making their way into production.
-
Machine Learning 2.0
Machine Learning 2.0, Deep Learning & Deep Learning Datasets.
-
Modern CS in the Real World
Applied, practical, & real-world dive into industry adoption of modern CS.
-
Optimizing Yourself
Maximizing your impact as an engineer, as a leader, and as a person.
-
Ask Me Anything (AMA)
