A set of exercises to prepare for Certified Kubernetes Application Developer exam by Cloud Native Computing Foundation
- kubernetes
- ckad
- certification
- ckad-exercises
47,133 repositories indexed
145–168 of 440 · Most stars
A set of exercises to prepare for Certified Kubernetes Application Developer exam by Cloud Native Computing Foundation
:page_facing_up: A curated list of awesome Angular resources
Resources for Blazor, a .NET web framework using C#/Razor and HTML that runs in the browser with WebAssembly.
A list of established remote companies
An awesome list of awesome YouTubers that teach about technology. Tutorials about web development, computer science, machine learning, game development, cybersecurity, and more.
🗺 The Android Developer Roadmap offers comprehensive learning paths to help you understand Android ecosystems.
:bathtub: Clean Code concepts and tools adapted for .NET
Awesome Object Detection based on handong1587 github: https://handong1587.github.io/deep_learning/2015/10/09/object-detection.html
Step-by-step guide through the abstract and complex universe of Fragment Shaders.
A Collection on all Jetpack compose UI elements, Layouts, Widgets and Demo screens to see it's potential
A collection of public resources about how software companies test their software
A collection of awesome security hardening guides, tools and other resources
Go DDD example application. Complete project to show how to apply DDD, Clean Architecture, and CQRS by practical refactoring.
ECMAScript 6: Feature Overview & Comparison
:dolphin: A comprehensive tutorial on getting started with Docker!
A comprehensive curated list of available Bug Bounty & Disclosure Programs and Write-ups.
A comprehensive Domain-Driven Design example with problem space strategic analysis and various tactical patterns.
An Open-Source Collection of Flash Cards to Help You Preparing Your Algorithms & Data Structures and System Design Interviews 💯
In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.
React: CSS in JS techniques comparison
A categorized list of C++ resources.
⭐️ A curated list of awesome forensic analysis tools and resources
A curation of prompts, plugins & other Fish treasures 🐚💎
:computer: :mortar_board: Git-it is a (Mac, Win, Linux) Desktop App for Learning Git and GitHub