Rust programming language course1/29/2024 A predictive model uses current data to predict an event, result, or outcome. You can either base those conclusions on classifications or predictions. Once you've trained your model, you can use it to draw conclusions from new data. Machine learning is the process of training a model to carry out tasks. Training a model is the process of giving data to the model to draw out patterns. In machine learning, a model is a software object that can understand patterns from data. To follow along with this tutorial you’ll need the following: And, machine learning engineers will find this tutorial useful in getting started with machine learning on Rust. Rust programmers will find this tutorial useful in getting started with machine learning. Although Rust doesn’t have a mature ecosystem, the programming language’s nature makes it perfect for applications that require speed and efficiency. Rust is a powerful and efficient programming language. Some machine learning applications may need to perform operations with great speed and computer resource efficiency. Languages like Python and R are excellent for learning and carrying out machine learning tasks. This reduces the need for programmers to hard code rules in some applications. It involves using data to train a computer program to carry out tasks.ĭuring the process, the program learns from data by discovering patterns. Thanks for writing it.Machine learning is a really interesting concept in computer programming. Thanks for the health statistics exercise.ĬXX: Instead of writing about Rust and C++ interoperability, I simply open the excellent tutorial in the class. Rust on Exercism: I copied an exercise from this excellent Rust course. Thanks in particular to the people working on the destructuring examples. I just made the pages shorter so they can be used in a classroom setting. Rust by Example: The format of the course is very similar to this excellent resource. We try to cover a majority of the material in the book. The Rust book: This served as a strong inspiration. It is an essential part of the interactive experience of the course. Thanks to and the other mainainers for keeping it running. The Rust Playground: the course uses it extensively via the embedded code snippets. I'll be sending more PRs your way in the next months. Mdbook: The course is built with mdbook and I'm grateful to for reviewing a small fix in preparation for the launch of the course. If you do, please let me know how it goes!īy the way, I hope this is a good place for me to say Thank You to the people who wrote the software we use in the course and who wrote documentation for Rust: If you're already proficient in Rust, it should be possible for you to pick up the course material and teach a class as your company. The course is ready to use for anyone: I've been teaching classes internally and we've also run classes with other instructors. Please use the issue tracker or the GitHub discussions to let me know about other missing topics - I'm sure there are lots of stuff we could cover We don't cover everything, though: I hope to cover async Rust soon, and we also need more material about interior mutability. We even touch upon unsafe Rust and we also have a chapter with Android-specific information. We start with basic syntax, borrowing, ownership, and move up to advanced topics such as generics, traits and error handling. To help accelerate the adoption of Rust in Android, we've written a four day course which aims to get developers started with Rust. I work on Android and we've supported Rust for OS level development for a couple of years now. You can find the source here: GitHub - google/comprehensive-rust. Hi all, I would like to share what I've been working on for the last few months at work: a new beginner-friendly Rust course called Comprehensive Rust.
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