Rust LLMOps

This video series is a rough draft course being updated JIT (Just in Time) and covers the Rust language through live coding. We offer an iterative approach to understand and master the language, particularly focusing on its application in MLOps.
Lesson 1: Embracing Automation and Tooling 1.1 A Function, the essence of programming 1.2 Operationalize Microservices 1.3 Continuous Integration for Microservices 1.4 What is Makefile and how do you use it? 1.5 What is DevOps? 1.6 Kaizen methodology 1.7 Infrastructure as Code for Continuous Delivery Lesson 2: Understanding Cloud Security 2.1 Responding to Compromised Resources and Workloads 2.2 Designing and Implementing Monitoring and Alerting 2.3 Audit Network Security 2.4 Rust Secure by Design 2.5 Preventing Data Races with Rust Compiler 2.6 Using AWS Config for Security 2.7 AWS Security Hub Demo Lesson 3: Understanding the GitHub Source Control Platform 3.1 Explain How to Secure Your Account with 2FA 3.2 Understanding Access Permissions 3.3 Repository Permission Levels Explained 3.4 Repository Privacy Settings and Options 3.5 Unveiling Key Concepts of the GitHub Ecosystem 3.6 Demo: Implementing GitHub Actions 3.7 Demo: GitHub Codespaces 3.8 Demo: GitHub Copilot Lesson 1: Introduction to Candle 4.1 Candle: A Minimalist ML Framework for Rust 4.2 Using GitHub Codespaces for GPU Inference with Rust Candle 4.3 VSCode Remote SSH development AWS Accelerated Compute 4.4 Building Hello World Candle 4.5 Exploring StarCoder: A State-of-the-Art LLM for Code 4.6 Using Whisper with Candle to Transcribe 4.7 Exploring Remote Dev Architectures on AWS Lesson 2: Rust for LLMs 5.1 Advantages of Rust for LLMs 5.2 Serverless Inference 5.3 Rust CLI Inference 5.4 Rust Chat Inference Lesson 3: Practical Applications of Candle 6.1 Continuous Build of Binaries for LLMOps 6.2 Chat Loop for StarCoder 6.3 Invoking Rust Candle on AWS G5 6.4 Invoking BigCode on AWS G5 Lesson 1: Getting Started With Rust Bert 7.1 Introduction to Rust Bert 7.2 Installation and Setup 7.3 Basic Syntax and Model Loading 7.4 Building a sentiment analysis CLI Lesson 2: tch-rs: Rust bindings for PyTorch 8.1 Introduction to Rust PyTorch 8.2 Running a PyTorch Hello World 8.3 PyTorch Pretrained 8.4 Running PyTorch Pretrained Lesson 3: Using ONNX 9.1 Introduction to ONNX 9.2 Onnx Conversions Lesson 1: Getting Started with GenAI Systems 10.1 Extending Google Bard 10.2 Exploring Google Colab with Bard 10.3 Exploring Colab AI 10.4 Exploring Gen App Builder Lesson 2: Beginning Generative AI Solutions in Cloud Computing 11.1 Responsible AI with AWS Bedrock 11.2 AWS Bedrock with Claude 11.3 Summaring text with Claude 11.4 Using the AWS Bedrock API Lesson 3: Exploring Generative AI Solutions with AWS CodeWhisperer 12.1 Live Coding AWS CodeWhisperer Part One 12.2 Live Coding AWS CodeWhisperer Part Two 12.3 Live Coding AWS CodeWhisperer Part Three