Learn Chrome-devtools, Npm and Python

You can’t be everywhere at once. Neither can node packages. But with a utility called npx — included in npm v5.2 and later — you can interact and run with node modules even if they’re not downloaded locally. The same is true for gists and remote branches of GitHub. As long as npm installed, your work can be wherever you are.

This course from Elijah Manor unlocks the power of the npx utility. Over 17 minutes, we will examine the npx package runner and look through various scenarios where the tool is helpful when running node packages from the command line. You’ll learn to use npm to:

- test out various versions of a package
- run packages without globally installing
- run code directly from GitHub
- make working with packages much easier

npm is the package manager for JavaScript. Find, share, and reuse packages of code from hundreds of thousands of developers — and assemble them in powerful new ways.

Execute npm Package Binaries with the npx Package Runner

Frontend runtime optimization is heavily impacted by rendering.  Understanding the way the JS engine and the browser work is crucial for optimizing applications and understading how to avoid performance pitfalls.
This collection explains about the Critical Rendering Path, performance bottlenecks and practical solutions.

JavaScript® (often shortened to JS) is a lightweight, interpreted, object-oriented language with first-class functions, most known as the scripting language for Web pages, but used in many non-browser environments as well such as node.js or Apache CouchDB. It is a prototype-based, multi-paradigm scripting language that is dynamic, and supports object-oriented, imperative, and functional programming styles.

javascript

Critical Rendering Path

Neural networks, with Keras, bring powerful machine learning to Python applications. They can answer questions like “How much traffic will hit my website tonight?” or answer classification questions like “Will this customer buy our product?” or “Will the stock price go up or down tomorrow?”

In this course, we’ll build a fully connected neural network with Keras. This is the most basic type of neural network you can create, but it’s powerful in application and can jumpstart your exploration of other frameworks. 

We’ll start the course by creating the primary network. Then we’ll:

- build and configure the network, then evaluate and test the accuracy of each
- save the model and learn how to load it and use it to make predictions in the future
- expose the model as part of a tiny web application that can be used to make predictions

You don’t need to know a lot of Python for this course, but some basic Python knowledge will be helpful. Enjoy!

Python is a widely used dynamically typed programming language. It allows for many different programming paradigms including object-oriented, imperative, functional programming, and procedural styles.

python

Fully Connected Neural Networks with Keras

Chrome DevTools are incredibly useful for a frontend developer, sometimes we spend more time using them than our text editor of choice.

That's why it's so important to understand this tool better - those quick lessons will teach you things that will help you to become a more effective developer.

You will learn how to:

- **Use (experimental) CSS Overview to learn all about CSS used on a page in a minute**
- **Style console.log messages with CSS** - a _crucial_ skill for any senior developer (j/k)
- **Debug your code (on production and local environment) with logpoints**
- **Run a Lighthouse audit of your site**
- **Choose accessible colors for your website that have an AAA contrast ratio rating**
- **Force a DOM element state in Chrome DevTools**
- **Use Console utilities to make debugging easier**
- **Copy a network request as fetch or cURL with Chrome DevTools**

Have fun!

The Chrome Developer Tools (DevTools for short), are a set of web authoring and debugging tools built into Google Chrome.

chrome-devtools

Chrome DevTools tips & tricks

In Introduction to Python, we will start at the beginning: Installing python 3 and using virtual environments. With a working environment, we will learn how to manipulate strings and numbers, and gain working knowledge of data structures and flow control. We will build on that by introducing modules and classes and learn how to interact with our python applications using command line switches, console input and files.

At the end of this course, you’ll have a great working knowledge of Python, fully capable of creating your own Python projects from scratch or jumping into an existing application with the capability to read, understand, and contribute to the application.

Check out these [**community notes for this course on Github**](https://github.com/eggheadio-projects/introduction-to-the-python-3-programming-language-notes).

Introduction to the Python 3 Programming Language

Artificial intelligence. Machine learning. Bots. Computers learning and communicating with us to do our bidding. But, where do you start? How do you get a machine to even begin to understand what you speak or type at it? There are several common machine learning algorithms that will help us begin to answer these questions.

In this course we’ll learn about common machine learning algorithms that don’t require implementing a neural network. We will not be going too much into the math behind them, but instead learn what each algorithm is good for, and how to train them. We'll also learn about a few metrics for evaluating models.

We’ll implement these in Python using `scikit-learn` using `scikit-learn`’s built-in data sets. The focus of this course is on implementation and a high-level understanding of these algorithms. 

We'll look at a few ways to evaluate our models, for both classification and regression models. We'll touch on mean squared error and coefficient of determination (for regression), and accuracy score, logarithmic loss, confusion matrices, and classification reports (for classification). 

Python 2.7 is used in the lesson videos but the code provided has Python 3 available. The only breaking change is the `print` statement API.

For additional information on installation, vocabulary, and common errors visit the `README.md` to the course code attached to each lesson.

Simple and efficient tools for data mining and data analysis

scikit-learn

Introductory Machine Learning Algorithms in Python with scikit-learn

npm is like a giant library of code building blocks. There are tons of these “blocks”, aka “packages” that we can compose together to build cool things. We can use packages by other developers, but we can also write and publish our own. 

In this course we will learn how to create, publish, and update our own packages. We will create a JavaScript utility module to filter out sensitive words from a string, including tests and development file watching. We will then cover publishing and updating our package. This same approach can be used to create and publish other types of packages too like components (React, Angular, Web Components etc.) and command line interfaces.

Publish JavaScript packages on npm

In this course we will introduce the topic of using npm scripts as a build tool. We will start simple and then continue to build a small website as we introduce new topics. By the end of the course, you'll know how to get started and what tools and techniques are needed for you to create your own set of build scripts.

How to Use npm Scripts as Your Build Tool

AWS Amplify allows developers to create, configure, and deploy Serverless APIs and functions directly from their front-end environment.In this collection, you'll learn how to deploy various types of APIs and functions using the Amplify CLI. You'll also learn how to share code among various functions using Lambda layers and schedule functions to run at an interval to implement Serverless cron jobs.

Up and Running with AWS Amplify Functions

In this course we’ll take a deep look at the Elements panel in the chrome devtools. We’ll step through each button and tab on this panel and discuss how to use them to interact with your web application as it runs.

Debug the DOM in Chrome with the Devtools Elements Panel

This course examines the Sources panel in the Chrome DevTools, which allows you to see what files are responsible for the various things on the screen. Bundled into this panel, though, is the single most useful tool for any JavaScript developer - the JavaScript Debugger. We’ll use the Debugger to inspect JavaScript as it runs, allowing you to watch (and even interact with) the state of your application as it runs in ways that’ll blow your mind if you’ve mostly used console.log to debug your applications to this point. 

Debug JavaScript in Chrome with DevTool Sources

This course will examine the Network panel in Chrome DevTools. We’ll step through the request log, examining the various properties exposed. We’ll talk about timing, filtering, throttling and generally using the network panel to better understand the ways in which our applications exist within a connected context.

Debug HTTP with Chrome DevTools Network Panel

If you are developing JavaScript applications you are likely using logging as an integral part of your development process. Did you know that you aren't limited to simple `console.log` statements? Modern browsers give you a lot more logging options to work with!

This course will explore those options and give you some new logging tools for your professional toolbox.

Advanced Logging with the JavaScript Console

Miscellaneous one-off lessons on debugging, productivity hacks, and JavaScript tricks.

Tips and Tricks

This is a small collection of videos to help you get familiar with Chrome browser's performance oriented developer tools.
In this collection, learn how to record a performance profile, tweak the settings to get the most relevant profile and finally a look into the different sections of the performance data visualisation.

Basics of Chrome's Performance Devtools

Anything related to JavaScript performance

Javascript Performance

Learn how to create tuples in Python. The videos in this collection will also cover more advanced features of tuples

The Ins and Outs of Python Tuples

React is one of the web’s most popular frameworks for building JavaScript applications. 

If you know what you’re doing, React can drastically simplify how you build, use, and maintain code.

Whether you’re a React newbie or you’re ready for advanced techniques, you can level-up with egghead. Explore our in-depth courses, lessons, and community resources to build more powerful applications and crack open your career.

react

Progressive Web Apps can speed up app loading times, and even allow you to run your web app offline, and install it on a mobile device!  However, setting up a PWA correctly can be tricky.

In this course, we'll create a PWA from start to finish, using create-react-app.  We'll create a custom service worker, and use different caching strategies for different types of assets.

Finally, we'll look at how to install the app on both iOS and Android devices, and how to customize the app name, icon, and splash screen.

Course Introduction: Progressive Web Apps in React with create-react-app

Your page is showing high CPU usage and spinning up your laptop fan, but nothing is visibly happening. What is it doing, and why is it so slow?

This lesson is a real-world performance diagnosis of this very page, right here on egghead. Two infinite (but hidden) animations were causing CPU usage to spike, and Chrome's Task Manager and Performance tools helped uncover the elements causing the problem. You'll see how to use the profiler to record a snapshot, and learn a trick for discovering animations running in the background.

Diagnose a Slow Page Using Developer Tools

Sometimes we'd like to ensure that some `console.log` are *really* visible one someone opens dev tools window. For instance, we could want to warn our less tech-savvy users that they shouldn't paste anything someone else send them to console, because their account might get stolen.

In this lesson we are going to learn how to style `console.log` messages with CSS properties so we can make our messages stand out from the crowd.

Style console.log messages with CSS

What's in a name? In this lesson, I'll explain the concept of naming interactive elements for screen reader users, including forms, buttons, and links. You'll learn how to debug accessible names and descriptions using the Chrome Accessibility Developer Tools (previously a Canary experiment, now in Chrome), using multiple labeling techniques. We'll also listen to the effects of proper accessible names and descriptions in Voiceover and Safari.

For more information and the nitty-gritty browser implementation algorithm, refer to WAI-ARIA 1.1: 
- https://www.w3.org/TR/wai-aria-1.1/#namecalculation
- https://www.w3.org/TR/accname-1.1/

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