Like Linux, Kubernetes consists of a core and an assortment of building block components that must be assembled and integrated to create an enterprise production-level platform. Most Kubernetes deployments fail because organizations underestimate the complexity of Kubernetes and overestimate their ability to deploy and manage a Kubernetes platform. In this webinar you will learn:
– The components and steps required to make Kubernetes an enterprise-level production-ready platform.
– The steps required to supplement AWS EKS to create an enterprise-level production-ready platform.
– How to create an enterprise Kubernetes platform that will accommodate continual innovation.
– The importance of an open Kubernetes solution.
– How to position your organization to be on the winning side of the smart cloud-native revolution. PUBLICATION PERMISSIONS:
Original video was published with the Creative Commons Attribution license (reuse allowed). Link: https://www.youtube.com/watch?v=NVN2631UaXM https://www.youtube.com/watch?v=PcuDTsVxrj8

WebAssembly opens the door for frontend developers to use languages that don't compile to JavaScript, like Rustlang. These technologies (rustlang yew) will change web development!! We use js-sys, web-sys, and friends to power this web application. 00:00 Introduction
00:04 What We'll Build (yew vp9 video streaming app)
00:41 Setup
01:19 Creating basic yew app structure
02:25 Running bare-bones app
02:42 How to call browser javascript frameworks from rust
03:26 Creating the skeleton of the yew app
05:06 Running the skeleton app
05:24 Connecting the WebCam
09:33 Testing Webcam with the Browser
09:57 Setting up the VP9 WebCodec Encoder
15:40 Things go sideways!! installing local libraries via cargo patch
18:14 Setting up the VP9 Encoder Part 2
20:40 Testing VP9 Encoding with the browser
21:03 Communicating Producer and Consumer using get_context
23:38 Connecting the Consumer to the Context
31:20 Debugging 33:54 Demo and Conclusions PUBLICATION PERMISSIONS:
Original video was published with the Creative Commons Attribution license (reuse allowed). Link: https://www.youtube.com/watch?v=In09Lgqxp6Y https://www.youtube.com/watch?v=lJllt5X6ELg

Bayesian statistical methods offer a powerful set of tools to tackle a wide variety of data science problems. In addition, the Bayesian approach generates results that are easy to interpret and automatically account for uncertainty in quantities that we wish to estimate and predict. Historically, computational challenges have been a barrier, particularly to new users, but there now exists a mature set of probabilistic programming tools that are both capable and easy to learn. We will use the newest release of PyMC (version 4) in this tutorial, but the concepts and approaches that will be taught are portable to any probabilistic programming framework. This tutorial is intended for practicing and aspiring data scientists and analysts looking to learn how to apply Bayesian statistics and probabilistic programming to their work. It will provide learners with a high-level understanding of Bayesian statistical methods and their potential for use in a variety of applications. They will also gain hands-on experience with applying these methods using PyMC, specifically including the specification, fitting and checking of models applied to a couple of real-world datasets. PUBLICATION PERMISSIONS:
PyData provided Coding Tech with the permission to republish PyData talks. CREDITS:
PyData YouTube channel: https://www.youtube.com/c/PyDataTV/videos https://www.youtube.com/watch?v=woXdiyezCPA