May 2023 | Created By Alfredo Deza, Noah Gift
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 28 Lessons 4 hours 9 minutes | Size: 1.23 GB
This video series covers how to switch to Rust from Python. It is in rough draft format and will be updated as the series progresses.
Course Outline Lesson 1: Introduction Lesson 2: High Performance MLOps with Rust Lesson 3: PyTorch, Stable Diffusion, and Rust GPU Demo Lesson 4: Google Cloud Platform and Rust Lesson 5: AWS and Rust
Introduction to Switching to Rust from Python
Rust Live Notes Overview
Setup Rust and Explain the Difference from Python
Copilot Enabled Rust Development
Leveling Up Rust Packaging, Actix Microservice, and Crates
Energy Efficiency of Python vs Rust
Using VS Code, Copilot and Codespaces to Level Up to Rust from Python
Continuous Integration and Continuous Delivery with Rust via GitHub Actions
Using All of GitHub's New Features: Copilot, Codespaces, Copilot Chat, and Copilot CLI
High Performance MLOps with Rust Hugging Face
Systems Programming Rust vs Python
Data Engineering with Rust - Deduplication
Rust GPU Hugging Face Translator
PyTorch Stable Diffusion Rust GPU Demo
High Performance PyTorch Rust Demo
Building a CUDA-enabled Stress Test with Rust PyTorch
Onboard GCP with Rust and Python
Google Cloud Run Rust Actix Microservice
Demo: Build and Deploy Rust Microservice to Cloud Run
Demo: Monitoring and Logging Rust App Engine
Demo: Load Testing
Intro to Actix Rust Containerized Microservice
Rust AWS Step Functions
MLOPs Inference with ONNX via EFS + AWS Lambda
Async Rust SDK with AWS Lambda counts all objects in S3
Rust for MLOps with Amazon SageMaker
Learning Objectives
Learn program in Rust using Python as a reference and advanced tools like GitHub Copilot to assist
Learning to build solutions with Rust including CLI, Web, and MLOps
Learning to build Rust solutions for AWS, GCP, and Azure
Learning to build Rust solutions for Kubernetes, Docker, and Serverless
Learning to build Rust solutions for Data Engineering, Data Science, and Machine Learning Operations (MLOps)
Learning to build Rust solutions for GPU-accelerated Machine Learning
Learning the key syntax and features of the Rust Language
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