Categories: AI/ML Research

Last call: Stefan Krawcyzk’s ‘Mastering MLOps’ Live Cohort



Last Updated on August 19, 2022

Sponsored Post

 

This is your last chance to sign up for Stefan Krawczyk’s exclusive live cohort, starting next week (August 22nd). We already have students enrolled from Apple, Amazon, Spotify, Nubank, Workfusion, Glassdoor, ServiceNow, and more.

Stefan Krawczky has spent the last 15+ years working on MLOps at companies like Stitch Fix, Nextdoor, and LinkedIn. He has successfully streamlined the model ‘productionalization’ process for hundreds of the best data scientists and machine learning engineers. He has also built and managed the infrastructure to create, deploy, and track tens of thousands of models using MLOps best practices. 

‍Over the course of 4 two-hour sessions with Stefan and other top ML professionals, you will:

  • Learn to identify, avoid, and prevent common ML outages
  • Review industry case studies to learn common approaches for scaling model inference
  • Evaluate and extrapolate tactics from Stitch Fix’s production deployment strategy
  • Discuss the best tooling for improving model observability

Plus, unlike other online platforms, these sessions on Sphere will give students the unique opportunity to work directly with Stefan on industry-specific scenarios to up-skill their MLOps knowledge while networking with other top-tier ML professionals. Since the course is also fully accredited, most students can expense the course using their employee L&D budget.

 
Learn more about Stefan’s live cohort now
 



The post Last call: Stefan Krawcyzk’s ‘Mastering MLOps’ Live Cohort appeared first on Machine Learning Mastery.

AI Generated Robotic Content

Recent Posts

Bringing Conversational Analytics to your entire data ecosystem

Increasing the adoption of generative AI across the enterprise requires you to do more than…

20 hours ago

OpenAI’s Rogue AI Agent Hacked More Than Just Hugging Face

In a new disclosure, OpenAI says its agent used exposed logins to gain access to…

21 hours ago

Brain-inspired AI is capable of flexible planning and problem-solving while using far less energy

The capabilities of large AI systems are constantly improving, but they consume a great deal…

21 hours ago

5 Architectural Patterns for Persistent Memory and State in AI Agents

Memory & State For AI Agents Building an AI agent can be tricky. Keeping it…

2 days ago

Teaching LLMs to Update Beliefs for Efficient Long-Horizon Interaction

Overview of ABBEL compared to traditional recursive summarization. Beliefs replace the full interaction history as…

2 days ago

GH-ESD: Grounded Hypothesis-Driven Error Slice Discovery for Instance-Level Vision Tasks

Systematic failures of vision models on semantically coherent subsets, known as error slices, reveal limitations…

2 days ago