Production debugging is hard, and it’s getting harder. With architectures becoming more distributed and code more asynchronous, pinpointing and resolving errors in production is no child's game. This session will cover advanced techniques that Java, Scala and Clojure developers can use to debug live servers and resolve critical errors in production quickly.We'll explore five crucial techniques for distributed and reactive logging, and some of the pitfalls that make resolution much more difficult (and even lead to downtime). We'll then dive into more advanced techniques and powerful tools for capturing live state from a production JVM without deploying new code, restarting the application or attaching a debugger.
Whether you’re a programmer with little to no knowledge of Python, or an experienced data scientist or engineer, this Learning Path will walk you through natural language processing, using both Python and Scala, and show you how to implement a range of popular tools including Spark, scikit-learn, SpaCy, NLTK, and gensim for text mining.
The course is designed for engineers and data scientists who have some familiarity with Scala, Apache Spark, and machine learning who need to process large natural language text in a distributed fashion.We will use sample of posts from the subreddit /r/WritingPrompts, which contains short stories and comments about the short stories.The course has four parts1. Building a natural language processing and entity extraction pipeline on Scala & Spark2.
Today, Wi-Fi is everywhere, and the need to provide good Wi-Fi is an essential part of doing business. But “good Wi-Fi” is not just about coverage or converting your APs to 802.11ac or 802.11ax. Good Wi-Fi means that your user experience is seamless. Most of the wireless networks today are designed to support only data applications and not real-time applications. In recent years, more and more companies are deploying real-time applications, and enterprise-quality is expected.
Reactive programming is shaping the future of how we model data. With reactive, not only can you concisely wrangle and analyze static data, you can effectively work with data as a real-time infinite feed. Reactive Extensions (Rx) first gained traction in 2009 and has been ported to over a dozen major languages and platforms.
You've tried to figure out what all those technical terms are all about (WTF is a reducer??) and you may even be convinced that you need a degree in Computer Science to be able to use Redux. You don't.
After taking this course, you can start mastering ExpressJS by building RESTful APIs for your single-page applications (powered by AngularJS, ReactJS, BackboneJS or any other front-end framework). With ExpressJS, developers can easily organize their code (middleware pattern), add more functionality (npm modules) and configure the server (configuration over convention).