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Nx
Elixir has steadily grown to become a viable and efficient language for machine learning, with an expanding ecosystem of libraries and tools. Nx, short for Numerical Elixir, is at the forefront of this surge, serving as a foundation for multidimensional array operations and facilitating machine learning tasks. Tensors, core units of data in Nx, can perform a wide range of mathematical computations essential for machine learning, including algorithms for both deep and traditional learning models.
Contributions by individuals such as Andres C Alejos and Sean Moriarity have significantly enriched the Elixir landscape with libraries like Bumblebee and Scholar. These tools provide capabilities comparable to their Python counterparts, allowing for tasks such as object detection and speech recognition. Furthermore, the intersection of Elixir's concurrent programming features with machine learning has presented intriguing possibilities for real-time applications in web environments, as highlighted by Philip Brown's work with Phoenix and LiveView.
Sean Moriarity's exploration into large-language models and open-source alternatives have underscored Elixir's expanding range and its potential for bespoke, cost-effective solutions. The language's evolution has been marked by key conferences like ElixirConf where practitioners share insights into machine learning applications such as spam detection, object detection, and production-model serving using Elixir-based solutions. Workshops and books dedicated to machine learning in Elixir, such as those by Sean Moriarity, demonstrate a growing interest in educational resources to bolster the community's expertise. Finally, the involvement of Elixir's creator, José Valim, and core team members in discussing future directions, underlines the community's commitment to advancing the language in harmony with machine learning.
Transition from Python Data Analysis to Elixir: A Case Study on Statistical Calculations
Written by Herminio Torres, this article talks about a journey from Python Data Analysis to exploring the Elixir Challenge with Nx and building a Mean-Variance-Standard Deviation Calculator.
Adoption of Elixir at Amplified: Productivity and Cost Benefits
In a detailed conversation, Chris Grainger, CTO of Amplified, shares his journey of adopting Elixir for his company, transitioning from Python and other languages. He discusses the significant benefits of Elixir's functional programming, LiveView, and the integration of Nx and ONNX. This shift led to remarkable improvements including halved AWS bills and reduced development team size while achieving more work.
Thinking Elixir Podcast Episode 180 Overview
This episode of the Thinking Elixir Podcast covers intriguing updates in the Elixir ecosystem, including a teaser from Chris McCord about Phoenix, Jose Valim's proposal for local accumulators, and the launch of a new Elixir library for node discovery using Postgres.
Discussion on 'Machine Learning in Elixir' Book
Sean Moriarity announces the release of a new book, 'Machine Learning in Elixir,' which aims to educate readers on leveraging Elixir and the Nx library for practical machine learning tasks, including computer vision and natural language processing.
Elixir Implementation of Machine Learning Book via Nx and Axon Livebooks
NickGnd shares an Elixir-based implementation of 'Programming Machine Learning' using Livebooks, Nx, and Axon.
Implementing Machine Learning with Elixir on Fly.io GPUs
Jason Stiebs provides an overview of using GPUs on Fly.io for real-world machine learning applications with Elixir, focusing on the implementation of a semantic search for Elixir's HexDocs.
Elixir's Practicality and Potential Beyond Web Development
Jason Stiebs touched on the practicality and power of Elixir, especially for web development and beyond. He recognized Elixir's leverage as an efficient, production-ready language with a solid ecosystem including Phoenix and observed a relative stability in his tech stack over years. He advocated for exploring Elixir's capabilities outside the traditional web domain, citing examples from machine learning to 3D modeling.
Translating Python NumPy Code to Elixir-Nx
Andrés Alejos presents an insightful article on converting Python's NumPy machine learning code to Elixir's Nx library.
Migration from React to LiveView for Enhanced Performance
This episode explores Tim Gremore's experience in significantly improving the performance of a React application by migrating it to a LiveView rendered page, leading to better scaling and user perception.
Overview of Recent Elixir News and Community Contributions
Mark Ericksen discusses recent community news including awards, book releases, AI and security updates in the Elixir ecosystem.
Exploring AI Integration in Elixir with Sean Moriarity
In episode 154 of the Thinking Elixir Podcast, the hosts discuss the intersection of AI and the Elixir programming language with special guest Sean Moriarity.
Transitioning from Ruby to Elixir - Steve Bussey's Insight
Steve Bussey discusses the mental model shift required when moving from OOP languages like Ruby to the functional paradigm of Elixir in his new book 'From Ruby to Elixir'.
Exploring Elixir's Interaction with WebAssembly through Orb
This episode of the Thinking Elixir Podcast discusses the Orb project, created by Patrick Smith, which is an Elixir DSL for WebAssembly and how it can be integrated into LiveView for improved user experiences.
Episode 164 - Elixir Community News Highlights
The episode covers important updates in the Elixir community such as the ElixirConf schedule release, Bumblebee's new streaming text support, Oban Web updates, a positive Elixir article on Hacker News, and examples of using Elixir Nx for AI.
Exploring Machine Learning's Evolution with Elixir Featuring Sean Moriarity
Sean Moriarity discusses the impact and future of Elixir in machine learning (ML) and artificial intelligence (AI), detailing the various technologies involved and highlighting the advantages of using Elixir for ML applications.
Discussion on Elixir's Future with José Valim
José Valim, creator of Elixir, talks about the language's future developments, community involvement, and hints at a potential typing system.
Discussing Elixir's Educational Path with Saša Jurić
Saša Jurić, the author of 'Elixir in Action', speaks about the progression and challenges in training and education for Elixir developers.
Discussions on Phoenix and Its Future Developments
Phoenix core team members Chris McCord and Jason Stiebs discuss key updates and future prospects of the Phoenix and LiveView with Elixir Wizards hosts Sundi Myint and Owen Bickford.
Discussing Elixir and Machine Learning with Sean Moriarity
In this episode of Beam Radio, the hosts engage in a conversation with Sean Moriarity about the intersection of machine learning and Elixir programming.
Comparing Machine Learning Capabilities Across Elixir, Python, SQL, and Matlab
Katelynn Burns and Alexis Carpenter discuss the state of machine learning in Elixir compared to Python, SQL, and Matlab in a recent Elixir Wizards podcast episode.
Elixir vs Python in Neural Network Performance and Development Experience
A. Neto and L. C. Tavano delivered a presentation on the comparison between Elixir and Python in terms of development experience and performance while working with simple neural networks.
Enhancing LiveView with Membrane for Realtime Media Processing
Lars Wikman, the founder of Underjord and a member of the BEAM Radio team, presents how the Membrane Framework can enhance LiveView with live video and audio capabilities. He discusses potential applications and the excitement of creating cool things by combining different inputs, transformations, and outputs.
Bringing Machine Learning Capabilities into Elixir with Bumblebee
Jonatan Klosko presents Bumblebee, an Elixir tool that simplifies using pre-trained machine learning models.
Elixir's Impact on Machine Learning and Production Workflows
Christopher Grainger explores the integration of machine learning in production within the Elixir ecosystem, highlighting the use of Nx, Livebook, and Scholar.
Three-Year Growth of Elixir's Nx Machine Learning Library
Sean Moriarity reflects on the growth and success of the Elixir machine learning ecosystem over the past three years. He discusses the unlikely start of the Nx project, the challenges faced, and the future of machine learning in Elixir.
Optimizing and Serving Large AI Models with Elixir and Nx
Toran Billups fine-tunes Mistral 7B using the RTX 4090 with limited vRAM, thanks to the open source Python project lit-gpt. He shares the steps required for fine-tuning and serving the model with Nx.
Building Scalable Machine Learning Applications with Elixir
Sean Moriarity shows how easy it is to build machine-learning applications with Elixir, especially in a few hours, to build a simple enriched newsfeed.
Summary of Machine Learning Developments in Elixir for Q3 2023
José Valim explores the latest developments in Elixir and Machine Learning in his blog post, highlighting the improvements in Nx, Explorer, Bumblebee, Scholar, and other projects. The future looks bright as optimization areas, like quantization and MLIR support, gain further attention.
Integrating Machine Learning Models with Elixir Using Nx
Andrés Alejos presents a talk at ElixirConf 2023 about using EXGBoost + Mockingjay, a Gradient Boosted Decision Tree library, in Elixir for learning structured tabular data and its application in a scalable production environment using Nx's Serving capability and a Phoenix web app.
Streamlining MLOps with Elixir's Capabilities
Sean Moriarity shows how to do MLOps in Elixir, simplifying the deployment of machine learning models without much effort.
Enhancing Machine Learning Decision Trees with Elixir
Andres Alejos created Mockingjay, a library designed to implement algorithms present in Microsoft’s Hummingbird for compiling tree-based machine learning algorithms into native Nx functions.
Exploring Motion Tracking in Elixir with Bumblebee and LiveView
Katelynn Burns presents the Thursday keynote at ElixirConf US 2023, Orlando, FL. She explores the fascinating and complicated movement of bodies, discussing how LiveView's open socket design and Bumblebee's neural network capability can be used to create motion magic.
Insights and Lessons from Phoenix Framework Development
Chris McCord shares his insights on new features coming to Phoenix at ElixirConf US 2023 in Orlando, FL.
Serving Spam Detection With XGBoost and Elixir
Learn how to detect spam with XGBoost and Elixir and serve the model for production use. Andres C Alejos shares their process and insights in this informative article.
Using Whisper for Speech Recognition in Elixir Applications
In this blog post, Sean Moriarity introduces Whisper, an audio-speech recognition model developed by OpenAI. He explains the challenges and uses of audio-speech recognition and provides instructions on how to use Whisper in Elixir applications with the help of the Bumblebee library.
Using Scholar for Traditional Machine Learning in Elixir
Sean Moriarity discusses traditional machine learning in Elixir with Scholar, a set of machine learning tools built on top of Nx. He explains how Scholar offers implementations of non-deep-learning models like linear regression and logistic regression, and demonstrates how to fit and visualize a linear regression model using Scholar in Elixir.
Elixir and Open-Source Alternatives to Proprietary LLMs like ChatGPT
In this blog post by Sean Moriarity, he discusses the rise of large-language models (LLMs) like OpenAI's ChatGPT and GPT-4, and explores open-source alternatives to these models. He highlights the benefits of using open-source models, such as data privacy, lower latency, task-specific performance, and cost considerations, and introduces some popular open-source options like Flan-T5, Llama, and OpenAssistant that can be used with Elixir.
Building a Video Object Detection Prototype with Elixir
Philip Brown has built a prototype of object detection in a video stream using Elixir, Bumblebee, and Phoenix LiveView. He provides a step-by-step guide on setting up the project, implementing object detection from a video, and building the LiveView application for displaying the video and predictions in the browser.
Tutorial on Recognizing Handwritten Digits with Elixir ML
In this tutorial by Philip Brown, you will learn how to build an end-to-end machine learning project using Elixir. The tutorial covers everything from setting up the project using Phoenix, obtaining training data, preprocessing the data, building and training the model, and finally, creating a LiveView to accept user input and display predictions.
Exploring Nx and Tensors Beyond Machine Learning in Elixir
This post by Jason Stiebs explores the use of NX with Elixir for efficient math programming. It explains how tensors can be used to perform various mathematical operations and highlights the potential of NX for tasks like machine learning and image manipulation.
From Python to Elixir Machine Learning
Andres C Alejos discusses the growth of Elixir's machine learning ecosystem and why now is a good time to start porting machine learning code into Elixir. He provides practical tips and examples for developers looking to move from Python to Elixir for machine learning projects.
Insights into Elixir's Machine Learning Libraries
Andres C Alejos provides an introduction to machine learning in Elixir and offers a glossary of libraries in the Elixir machine learning ecosystem. He covers libraries such as Elixir-Nx, Axon, Bumblebee, Scholar, Explorer, Scidata, EXGBoost, Ortex, Livebook, and more, highlighting their functionalities and similarities to popular Python libraries.
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