Learn Python, Redwoodjs and Rust

Rust is a modern language that is close to the metal. It's got the performance of C, but with a more friendly syntax and community.

It's also memory safe, and ensures your applications are bug free by catching errors at compile time instead of runtime.

These features make Rust a great choice for developing code for embedded systems, web servers, and CLI apps. You can even compile Rust into WebAssembly in order to run it in-browser!

But as the saying goes, "before you learn to run, you must learn to walk".

In this course, you will write your first Rust application.

Starting from “Hello World” you’ll quickly move on to learning about Rust’s types, configuration files, and the `cargo` package manager along with classics like functions, loops, and handling user input.

More Rust-specific concepts like macros and pattern matching will also be introduced.

Check out these [**community notes for this course on Github**](https://github.com/eggheadio-projects/write-your-first-program-with-the-rust-language).

Next Steps: [Basic Types in Rust](https://egghead.io/playlists/data-types-in-rust-ab72)

Rust is a systems programming language that runs blazingly fast, prevents segfaults, and guarantees thread safety.

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Write Your First Program with the Rust Language

[Rustlings](https://github.com/rust-lang/rustlings) is a set of exercises that serves as a great introduction to the Rust language. It covers many concepts from the [Rust book](https://doc.rust-lang.org/book/) by asking you to work through sets of exercises.

This collection walks you through Rustlings in a way that explains what's going on in each exercise. We cover everything from basic types to generics and threading.

Learning Rust by Working Through the Rustlings Exercises

This collection contains videos that explore the basic types in Rust, including **Fixed size Integer**, **Pointer sized Integer**, **Boolean**, **Strings**, **Characters**, **Arrays**, **Tuples** and more.

If you're just starting out learning Rust and [wrote your first program](https://egghead.io/courses/write-your-first-program-with-the-rust-language), this collection is the right place to get more familiar with the language!

Basic Types in Rust

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

Many languages work on a compilation story to WebAssembly, but Rust is already ready for primetime. Why?


- Rust is a stable language and great replacement for C and C++. 
- Due to the reference and borrowing concept, Rust doesn’t need a Garbage Collector and can be used for a production-ready WebAssembly project. 
- The Rust/Wasm team has built some sophisticated tooling for straightforward interoperability between Rust and JavaScript.

This course gives you the tools to compile to WebAssembly with Rust. Over 11 lessons, we’ll set up a project and explore various paths of communication and interoperability between Rust and JavaScript.

Using WebAssembly with Rust

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

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

RedwoodJS takes the JAMstack philosophy to the next level. It brings together all the tools modern web development has to offer:

- React
- GraphQL
- Prisma

RedwoodJS abstracts database management away from you so that you can just build your schema and it will do all the plumbing. This collection will go over how to create a RedwoodJS project and the scripts that will help make your developer experience a joy.


Bringing full-stack to the JAMstack

Do you love the JAMstack philosophy but need a database-backed web app? Want great developer experience and easy scaling? Redwood is here! Built on React, GraphQL, and Prisma, Redwood works with the components and development workflow you love, but with simple conventions and helpers to make your experience even better.

redwoodjs

Introduction to RedwoodJS: full-stack framework for JAMstack

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 we’ll create a new Rust project using the `cargo new` command and take a look at some of the generated files.

Create a Rust package with the Cargo package manager

In this lesson you'll learn how to install Rust's toolchain.

Install Rust

In this lesson we’ll create our first “Hello World” Rust program from scratch and will learn how to compile it using `rustc`.

Compile and run a Rust program from scratch

In this lesson we'll learn how to use the `cargo run` command to compile and run a Rust program.

Compile and run a Rust program using Cargo

In this lesson we'll learn how to initialise variables in Rust and how to make them mutable using the `mut` keyword so they can be changed throughout the program.

Variables and Mutability in Rust

In this lesson we take a look at how `println!()` can be used to output multiple variables using formatter placeholders.

Output multiple variables using println!() in Rust

In this lesson we'll create a new function that receives parameters and called inside our program's `main()` function.

Write and call a function in Rust

In this lesson we'll briefly discuss the concept of Ownership and Borrowing in Rust, and how expressions can be passed by value and by reference.

Understanding basic Ownership and Borrowing in Rust

In this lesson we'll learn how to read user input from stdin, using Rust's `std::io` module and its `Stdin` object.

Read user input from stdin in Rust

In this lesson we'll take a look at the simplest way of handling error in Rust using the `unwrap()` function.

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