Learn Egghead, Protractor and Python

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

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

Tips and Tricks

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.

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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.

Up and Running with AWS Amplify Functions

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

Misunderstanding scope can cause problems in your application. Watch this lesson to learn how Python scope works and the hidden implications it presents. Local scope, nonlocal scope, and global scope variables are demonstrated and explained.

Understand Scope in Python

A module is a function extracted to a file. This allows you to import the function and use it in any other code you may write. You’ll learn how to create modules, import them, and make them stand-alone as you learn what `if __name__ == “__main__”` means in Python.

Reuse Code in Multiple Projects with Python Modules

Why should you have to write all the code? Why can’t you leverage code written by others? I’ve got great news: you can. You’ll learn how to search pip, Python’s package installer, to find and install packages to add new features and functionality to your application.

Manage packages with pip in Python

Object oriented classes work much like classes in other languages. Learn how to create them and use them, learn the difference between class variables and instance variables, creating class methods, and learn how to create classes that inherit from other classes.

Use Python Classes

Any extra information on the screen will easily distract the audience from the purpose of your lesson. Do your best to remove any extra notifications, UI, or other information that would take away from what you're teaching.

Remove Distractions

Any information you would want to put into an Intro or Outro belongs in the accompanying description, title, course page, etc. The lesson is only for showing the process. Talking about yourself, the lesson, or other lessons is a waste of time.

Avoid Intros and Outros

Tangents are opportunities for other lessons. When you find yourself drifting off-topic because you feel you _need_ to explain  some code you wrote, consider how that piece of code fits back into a "How do I?" question, then come up with a separate lesson to capture it.

Stay on Topic

Recording can be intimidating, so it's best to just hit the record button and start talking. Take it one thought at a time. Sit quietly, think about what you're going to say/type, then do it. If you mess, up, undo back to when you were quiet and try again. Once you get a good take, move on to the next thought. The ideal raw recording is a ton of bad takes and one good take for each thought. So when you get to the editing phase, you quickly clear out the bad takes and leave the good ones.

Record One Thought at a Time

Editing a raw lesson video is a very simple process. You simply watch your own lesson and edit out all the bad takes and dead space using the "Ripple Delete" command. You will be left with a nice, cut lesson ready to export and upload.

Edit with Ripple Delete

Video is a one-way form of communication, so user's don't have the chance to ask you to clarify or ask "Where does X fit in?" This places the burden on you to guide their eyes as you explain how all the little pieces of the code fit together. When your application has a "flow", "X triggers Y, Y triggers Z", make sure to "show the flow" by walking them through where each chunk of code fits. This involves a lot of mouse movement (or fancy keyboard selection shortcuts) and hightlighting to bring it all together.

Guide Their Eyes

Getting input from the user via a console command can be done with `input` in Python. Learn how to implement it and validate user input in this lesson.

Read Input in Python from the Console

Exceptions cause your application to crash. Handling them allows you to recover gracefully and keep your application running. Learn how to handle exceptions, find what exceptions you should be handling, and exit gracefully in this lesson. You will also learn how you should *not* handle exceptions and when it is better to let your application crash rather than swallowing an exception. 

Handle Exceptions to prevent crashes in Python

This lesson will introduce arithmetic operations in Python. In addition to basic addition, subtraction, multiplication, and division, you will learn about the differences in division between Python 2 and Python 3.

Perform Math Operations in Python

The tuple is a new data structure to Python, and is an immutable sequence of values separated by commas. Learn how to create them in this lesson.

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Free or Pro