Opening book details…
Can I read Machine Learning in Elixir on EtoBox?
Machine Learning in Elixir by Sean Moriarity is a nonfiction available to read on EtoBox.
What is Machine Learning in Elixir about?
Stable Diffusion, ChatGPT, Whisper - these are just a few examples of incredible applications powered by developments in machine learning. Despite the ubiquity of machine learning applications running in production, there are only a few viable language choices for data science and machine learning tasks. Elixir's Nx project seeks to change that. With Nx, you can leverage the power of machine learning in your applications, using the battle-tested Erlang VM in a pragmatic language like Elixir. In this book, you'll learn how to leverage Elixir and the Nx ecosystem to solve real-world problems in computer vision, natural language processing, and more. The Elixir Nx project aims to make machine learning possible without the need to leave Elixir for solutions in other languages. And even if concepts like linear models and logistic regression are new to you, you'll be using them and much more to solve real-world problems in no time. Start with the basics of the Nx programming paradigm - how it differs from the Elixir programming style you're used to and how it enables you to write machine learning algorithms. Use your understanding of this paradigm to implement foundational machine learni
Who reads Machine Learning in Elixir?
It is typically read by self-directed learners exploring a subject in depth.
Common subject areas: history, science, philosophy, social sciences.
- Author
- Sean Moriarity
- Publisher
- The Pragmatic Bookshelf, LLC
- Published
- 2024
- Language
- EN
- ISBN
- 9781680506204
- Category
- nonfiction
- Subjects
- Computer Science, Programming, Artificial Intelligence (Ai)
Other editions & translations
More by Sean Moriarity
Browse all works by Sean Moriarity
Similar books
- Machine Learning in Java : Design, Build, and Deploy Your Own Machine Learning Applications by Leveraging Key Java Machine Learning Libraries — Bos̆tjan Kaluz̆a (2016)
- Machine Learning Automation with TPOT: Build, Validate, and Deploy Fully Automated Machine Learning Models with Python — Dario Radečić (2021)
- Statistical Modeling in Machine Learning : Concepts and Applications — G. R. Sinha Tilottama Goswami (2022)
- Adversarial Machine Learning — Yevgeniy Vorobeychik, Murat Kantarcıoğlu, Murat Kantarcioglu (2018)
- Machine Learning in Python — Robert Karamagi (2021)
- Graph-Powered Machine Learning — Alessandro Negro (2021)