Daniel Hinojosa
Independent Consultant
Daniel is a programmer, consultant, instructor, speaker, and recent author. With over 20 years of experience, he does work for private, educational, and government institutions. He is also currently a speaker for No Fluff Just Stuff tour. Daniel loves JVM languages like Java, Groovy, and Scala; but also dabbles with non JVM languages like Haskell, Ruby, Python, LISP, C, C++. He is an avid Pomodoro Technique Practitioner and makes every attempt to learn a new programming language every year. For downtime, he enjoys reading, swimming, Legos, football, and barbecuing.
Presentations
Machine Learning Data Pipelines
Monday, 9:00 AM EST
This workshop builds an entire event driven data pipeline with Machine Learning and Kafka. From Kafka where we use producers or Kafka Connect to generate information, we then will Kafka Streams to apply a machine learning model to make business decisions.
This intensive lab will start by integrating sources into our backplane, then train our models, and operationalize our model using Kafka Streams. We will then create result topics when we can read in as a report and display visualizations of our data. The result will also be scalable and fault tolerant.
Java Design Patterns Deep Dive
Tuesday, 1:00 PM EST
Since 1994, the original Gang of Four Design Patterns book, “Design Patterns: Elements of Reusable Object-Oriented Software” has helped developers recognize common patterns in development. The book was originally written in C++, but there have been books that translate the original design patterns into their preferred language. One feature of “The Gang of Four Design Patterns” that has particularly stuck with me has been testability for the most part. With the exception of singleton, all patterns are unit testable. Design Patterns are also our common developer language. When a developer says “Let's use the Decorator Pattern” we know what is meant.
What's new though is functional programming, so we will also discuss how these patterns change in our new modern functional programming world. For example, functional currying in place of the builder pattern, using an enum for a singleton and reconstructing the state pattern using sealed interfaces. We will cover so much more, and I think you will be really excited about this topic and putting it into practice on your own codebase.
Java Design Patterns Deep Dive
Tuesday, 3:00 PM EST
Since 1994, the original Gang of Four Design Patterns book, “Design Patterns: Elements of Reusable Object-Oriented Software” has helped developers recognize common patterns in development. The book was originally written in C++, but there have been books that translate the original design patterns into their preferred language. One feature of “The Gang of Four Design Patterns” that has particularly stuck with me has been testability for the most part. With the exception of singleton, all patterns are unit testable. Design Patterns are also our common developer language. When a developer says “Let's use the Decorator Pattern” we know what is meant.
What's new though is functional programming, so we will also discuss how these patterns change in our new modern functional programming world. For example, functional currying in place of the builder pattern, using an enum for a singleton and reconstructing the state pattern using sealed interfaces. We will cover so much more, and I think you will be really excited about this topic and putting it into practice on your own codebase.
Machine Learning Data Pipelines
Tuesday, 5:00 PM EST
How do we move information realtime and connect machine learning models to make decisions on our business data? This presentation goes through machine learning and Kafka tools that would help achieve that goal.
In this presentation, we start with Kafka as our data backplane and how we get information to our pub/sub. As they enter Kafka, how do we sample that data and train our model, then how do we unleash that model on our real-time data? In other words, picture extracting samples for credit card approvals for training, then attaching the model for online processing: The moment we receive an application, we can either approve or disapprove a credit application based on a machine learning model trained on historical data. We will discuss other options as well like Spark, H2O, and more.
Books
Testing in Scala
by Daniel Hinojosa
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If you build your Scala application through Test-Driven Development, you’ll quickly see the advantages of testing before you write production code. This hands-on book shows you how to create tests with ScalaTest and the Specs2—two of the best testing frameworks available—and how to run your tests in the Simple Build Tool (SBT) designed specifically for Scala projects.
By building a sample digital jukebox application, you’ll discover how to isolate your tests from large subsystems and networks with mocking code, and how to use the ScalaCheck library for automated specification-based testing. If you’re familiar with Scala, Ruby, or Python, this book is for you.
- Get an overview of Test-Driven Development
- Start a simple project with SBT and create tests before you write code
- Dive into SBT’s basic commands, interactive mode, packaging, and history
- Use ScalaTest both in the command line and with SBT, and learn how to incorporate JUnit and TestNG
- Work with the Specs2 framework, including Specification styles, matchers DSLs, and Data Tables
- Understand mocking by using Java frameworks EasyMock and Mockito, and the Scala-only framework ScalaMock
- Automate testing by using ScalaCheck to generate fake data