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All LessonsFree Lessons (5)

Before We Begin

What to Expect in This Course

Rust Data Structures

Arrays and Slices Vectors and Strings HashMaps HashSets Structs

Course Assessment

Rust Data Structures

Basics of Functional Programming

Functions vs Closures Iterators Higher-order Functions: Rust's Secret Sauce Higher-order Functions: Part II

Course Assessment

Functional Programming in Rust

Data Skill: Input Data

Working with Files and the OS CSV: Comma Separated Values JSON: The de Facto Web Data Standard Fetching Data on the Internet Poll Data Services through APIs The Basics of Web Scraping

Course Assessment

Input Data with Rust

Mini Project

Web Scraping: Getting Products and Prices from an E-commerce Site

Data Skill: Store Data

Redis Sqlite Relational Databases (SQL): MySql, Postgres, SQLite MongoDB MongoDB: Part II

Course Assessment

Storing Data in Rust

Mini Project

Create a Simple Payroll Management System

Data Skill: Serve Data

Server Basics A CRUD Server Other Data Servers

Course Assessment

Serving Data in Rust

Mini Project

Build a Server Backed Up by a Database

Data Skill: Analyze Data

The Matrix and ndarray Polars Smartcore

Course Assessment

Assessment on Analyze Data

Mini Project

ML Basics: Classification of the Iris Data Set

Mini Project

Machine Learning and the MNIST Digit DataSet

Data Skill: Dataviz and Storytelling

The Basics of Data Visualization Maps The Basics of Storytelling through Data with Rust

Course Assessment

Data Viz and Storytelling in Rust

Mini Project

Create Infographics in Rust

Some Parting Words

Congratulations!

Processing Real-world Data Efficiently with Rust/

ML Basics: Classification of the Iris Data Set

The Iris dataset is one of the most famous beginner’s data science and machine learning datasets. It includes 150 entries of 3 classes of flowers, with 50 examples for each, and is used primarily to learn how to apply a classification algorithm.

Image courtesy of Nicoguaro, CC BY 4.0, on Wikipedia

We’ve already seen how to use this dataset with smartcore. However, in this project, we’ll learn how to create a simple classifier from scratch.

Are you ready to learn?