Learn Cycle, Mobx 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

Developing logic-rich applications is a key skill to have.

The TypeScript–React combination helps you unlock that skill, and it’s a great developer experience in terms of writing understandable and refactorable HTML. But the default state management for React has a long way to go to feel simple and maintainable — and that’s where MobX makes your life so much easier. MobX keeps things simple without using complicated setups like `provider` and `connect` that provide way too little value for all the mental overhead. 

In this course, you’ll see how to model your React application logic using simple JavaScript classes — and with the help of MobX, make those classes the beating heart of your React applications. You’ll learn:

- that you don't need advanced annotations and TypeScript features to use MobX
- how to easily refactor code through TypeScript
- how to use TypeScript to track the flow of state as properties change

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.

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Develop React Applications with Mobx and TypeScript

MobX State Tree (MST) is a library that helps you organize your application states in a very structured manner. It allows you to create a component model, but for your data!

Course instructor Michel Weststrate—creator of Mobx—will teach you to model application state after your problem domain with MST. You will get hands-on practice and see how MST lets you solve problems with its out-of-the-box support for asynchronous actions, patches, snapshots, and middleware.

Over the 17 lessons, you’ll build a little bookshop application using React, MST, and create-react-app, while learning how to manage the lifecycle of your data by describing data models. 

Join Michel in one of the most popular courses on egghead!

Manage Application State with Mobx-state-tree

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

Cycle.js is a framework where your app is described as a simple function taking an event stream as input and outputting an event stream. 

Cycle.js builds on functional and reactive streams and is a JavaScript framework. What does that mean? In the course, André Staltz, the creator of Cycle.js, will explain it to us.

We'll start this course with an empty project and build out our own toy version of Cycle.js to understand exactly what's going on under the hood. When we have a solid base of how Cycle.js works we will move on to use the Cycle.js API and build an app using the Model-View-Intent pattern.

Cycle.js is a framework where your app is described as a simple function taking an event stream as input and outputting an event stream.

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Cycle.js Fundamentals

MobX is designed to enable building web applications with a complex data model in an intuitive and very performant manner. Using React and MobX is currently the simplest way to build component based web applications.

"Half the code, twice the fun" is how people describe MobX, or "So simple, I cannot believe it just works". 



Manage Complex State in React Apps with MobX

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

Since MST offers a runtime type system, it can create and compose types on the fly, making it possible to reuse logic in new and powerful ways.

In this lesson you will learn:
* That MST types are immutable and composed together behind the scenes
* How to compose types explicitly by using `types.compose`
* How to create dynamic, parameterized types by leveraging that MST types are first class javascript citizens

Create Dynamic Types and use Type Composition to Extract Common Functionality

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

We are starting to get a better architecture for these UI apps. But we still have a problem of repeating code for the sliders, since they share so much in common in looks and functionality. This lessons shows how we can create a generic labeled slider as a main() function receiving properties as sources.

Create a Generic Cycle.js Component

Applications are driven by state. Many things, like the user interface, should always be consistent with that state.
[MobX](https://mobxjs.github.io/mobx) is a general purpose FRP library that provides the means to derive, for example, a React based user interface automatically from the state and keep it synchronized.

The net result of this approach is that writing applications becomes really straight-forward and boilerplate free.

Sync the UI with the app state using MobX observable and observer in React

This lesson explains how you can build larger trees of react component and how they are managed efficiently by MobX. You will learn how to pass observable data structures around in props and how the Devtools can be used to analyze the performance of your UI.

Pass observable data through props in MobX

This lesson explains how actions can be used to control and modify the state of your application. They help you to structure your code base and integrate well with the MobX React Devtools. Actions automatically create transactions, which group changes together.

Use MobX actions to change and guard state

Our app is not yet a BMI calculator, because it only has two sliders, but doesn't show the calculated BMI number. In this lesson we will learn how to export any stream from a child component and use it in the parent component, in order to display the BMI calculation on the DOM.

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