Learn Egghead, Protractor and Python

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.

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Fully Connected Neural Networks with Keras

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

This is the video companion to the [egghead.io Instructor Guide](https://howtoegghead.com/instructor/).

Screencasting is hard! There are virtually infinite ways to produce one. For an egghead.io lesson we expect several key aspects to be met. We want to make sure that our lessons have depth and clarity. Clarity is important and starts with the technical aspects of recording your screen and voice. Once we have achieved this objective level of clarity, we dip into the stylistic aspects of recording a lesson. The style is subjective, and the goal of an egghead.io lesson is not to have an army of uniform drone producing flavorless video content for the masses.

Our mission is to make you a badass screencaster. We want to push you to another level. We've found that a small set of standard practices will create an awesome experience for the student, and eliminate frustration as we teach by providing a repeatable pattern for success. It’s not complicated. In fact, it is simple, but it isn’t easy.


This course will show you how to produce an egghead.io lesson. We strive for consistency in style, and these lessons will demonstrate the core elements that create our brand screencasts. Let’s learn how together.

Bite-size video tutorials for badass web developers.

egghead

Record Badass Screencasts for egghead.io

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.

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.

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Up and Running with AWS Amplify Functions

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

Tips and Tricks

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

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

chrome-devtools

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

codesandbox.io provides one of the fastest ways to start a new React project. In this lesson, we will take a first look at codesandbox, its interface, and the default React project it creates.

Use Codesandbox to Start a New React Application

By re-assigning a couple mouse buttons, you can drastically improve the speed you can edit your lessons in Screenflow. This lesson shows how to customize using the Logitech software, but the concept should work for any mouse customization software as well.

Faster Edits in Screenflow with Mouse Customizations

Sometimes you have an idea that you want to quickly record, but the idea of setting up a project just to get it recorded gets in your way. I'm going to walk your through scripting away the main setup pain points so that you can focus on creating content.

Automate egghead Lesson Setup with ZSH Shell Functions

Sometimes you get strings instead of objects and you have to parse them out. Here's an example where the raw data I got from a Twitch chatbot message wasn't useful to me until I parsed it into a dictionary.

Turning a key/value string into a dictionary in Python

When making your font sizes large, your code will often get to long to fit on the screen. This lesson shows you how to use "word wrap" or "prettier print width" to adjust your code to fit within the editor.

Reformat Code to Fit the Screen

Visual Studio Code is an integrated development environment (IDE) built and maintained by Microsoft. It is offered free of charge.

vscode

In this lesson, we will learn how to use custom ENV variables to customize the PS1 Bash/Zsh command prompt in the VS Code terminal, without affecting our custom terminal themes in other applications. We will see how this can be useful for keeping the terminal clean for screen recordings.

I'm using Zsh in this video, but this works in Bash with `~/.bashrc` as well.

Customize the PS1 Bash/Zsh Command Prompt in VS Code with Environment Variables

Lessons often have common starting points. If you're going to make lessons in bulk, it helps to create templates so you don't waste time setting them up over and over.

Create a Lesson Template

Once your lesson template is ready, it's time to create some github repos to share your code. The easiest way to do this is with Github's CLI tool called "hub".

Create Repos on Github from the CLI with hub

ZSH allows you to write functions to wrap around common commands. These allow you to easiest invoke a number of lesson creation steps by only typing out the command.

Automate Lesson Creation From Templates With ZSH Functions

Forgetting to pass an argument to a zsh function could result in creating unnecessary folders or cloning code you didn't mean to. It's best to check for arguments to prevent unwanted results.

Add Conditions to ZSH Functions to Prevent Mistakes

Once you've finished your demo locally, it's time to commit, push it to github, and share your demo online. This zsh function breaks it down into a single call.

Branch and Create a Lesson in a Single ZSH Function

Alfred is a super speed booster when it comes to common tasks. If you're going to be creating a lot of lessons from templates, Alfred can save you from even opening your terminal.

Select a Lesson Template From an Alfred Workflow

Using Alfred, you can map a global keyboard shortcut to the process of cloning a lesson template repo and firing up your demo.

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