Learn Hapi, Python and Tachyons

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

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Introductory Machine Learning Algorithms in Python with scikit-learn

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

hapi is a battle-tested, full-featured, framework for building web applications and services with Node.js. With integrated support for essentials like authentication, caching and validation, and a powerful plugin system, hapi is ideal for projects and teams of any size.

This course will introduce hapi, some of it’s plugins, and guide you through many of hapi’s core features.

A rich framework for building applications and services hapi enables developers to focus on writing reusable application logic instead of spending time building infrastructure.

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Introduction to Node Servers with Hapi.js

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

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

In this lesson, you'll learn how to deploy a serverless function using the Python runtime, connect it to an API endpoint, and interact with it from a React application.

Creating a full stack serverless app with Python, React hooks, and AWS Amplify Functions

Using the `open` function, and the `as` and `with` keywords, we'll open up and read from a file. At the end of this lesson, you will be able to loop through the lines of text in a file, process the text in Python, and then print them to the terminal.

Read from a File in Python

Learn how to create a tuple in Python. A tuple is an immutable data type that contains several items similar to a list. Items in a tuple can be of any data type.

Create a Tuple in Python

Learn to create a one item tuple. When creating a one item tuple, a comma has to be included after the item. Otherwise, your tuple will not return tuple as its data type. 

Create a One Item Tuple in Python

Tuples are immutable so there is no way to add or replace items in tuples. There is a way to get around this by adding two tuples into one. 

Understand Immutability with Python Tuples

View engines, or template engines, allow you to maintain a clean separation between your presentation layer and the rest of your application. This video will demonstrate how to use the vision plugin with hapi to enable template support.

hapi.js - View engines 

hapi does not support serving static files out of the box. Instead it relies on a module called Inert. This lesson will cover serving static files using Inert's custom handlers.

hapi.js - Serving static files

Routing is a fundamental aspect of any framework. In this lesson, you'll learn how to use path parameters in hapi's router. We'll also touch on how the router uses specificity to order routes internally.

hapi.js - Route parameters

hapi doesn't ship with logging support baked in. Luckily, hapi's rich plugin ecosystem includes everything needed to configure logging for your application. This video will introduce good, a process monitor for hapi, and good-console, a reporter for good that outputs to standard out.

hapi.js - Logging with good and good-console

hapi makes handling POST and PUT payloads easy by buffering and parsing them automatically without requiring additional modules or middleware. This video will demonstrate how to handle JSON and form based request payloads via hapi's route configuration.

hapi.js - POST and PUT request payloads

hapi's reply interface is one of it's most powerful features. It's smart enough to detect and serialize objects, buffers, promises and even streams. This video will demonstrate first hand how to use the reply method to send your data to the client, no matter the format.

hapi.js - Replying to Requests

Think of hapi's `reply()` function as "what you want to say" and the `response` object as "how you want to say it". While `reply` controls the payload sent to the client, the `response` object will allow you to control how the client interprets the payload by manipulating status code, content type, state and more.

hapi.js - Using the response object

hapi automatically responds with JSON for any error passed to a route's `reply()` method. But what if your application needs errors rendered in HTML? This lesson shows how to implement friendly HTML error messages using hapi extension events.

hapi.js - Friendly error pages with extension events

hapi supports request validation out of the box using the joi module. Request path parameters, payloads, and querystring parameters can be validated with joi's simple, yet powerful, notation. This lesson covers the basics of validating requests using joi.

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