The Little Elixir & OTP Guidebook gets you started writing applications with Elixir and OTP. You'll begin with the immediately comfortable Elixir language syntax, along with just enough functional programming to use it effectively. Then, you'll dive straight into several lighthearted examples that teach you to take advantage of the incredible functionality built into the OTP library.
Machine Learning Platform Engineering shows you how to build an effective IDP for ML and AI applications. Each chapter illuminates a vital part of the ML workflow, including setting up orchestration pipelines, selecting models, allocating resources for training, inference, and serving, and more. As you go, you’ll create a versatile modern platform using open source tools like Kubeflow, MLFlow, BentoML, Evidently, Feast, and LangChain.
Putting machine learning into production can often be a complex task. The Kubeflow platform helps streamline this process with simple and scalable ML workflow deployment. In this liveProject, you’ll put Kubeflow into action to help your team roll out their new license plate recognition deep learning system.
You’ll help data scientist colleagues by standardizing their working environment, and automating away many tedious and error-prone tasks. Your challenges will include restructuring a complex deep learning project to make it Kubeflow-friendly, and developing reusable components that can be transferred to other machine learning pipelines.
The Little Elixir & OTP Guidebook gets you started writing applications with Elixir and OTP. You'll begin with the immediately comfortable Elixir language syntax, along with just enough functional programming to use it effectively. Then, you'll dive straight into several lighthearted examples that teach you to take advantage of the incredible functionality built into the OTP library.