ML Workflow Challenges
The discussion highlights the intersection of machine learning workflows and software engineering challenges, emphasizing the gap between academic research and industry practices. Arun shares insights from conversations with industry experts, pointing out the need for a collaborative approach to address common challenges and develop more effective tools. He advocates for practitioners to identify broader questions that could inform research and enhance the overall ML ecosystem.In this clip
From this podcast
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
The New DBfication of ML/AI with Arun Kumar - #553
Related Questions
What are the challenges in machine learning?
What are the challenges in machine learning as discussed in the episode MLOps - Design Thinking to Build ML Infra for ML and LLM Use Cases // Amritha Arun Babu & Abhik Choudhury // #221 and the clip Data Scientist Challenges?
What are the challenges in machine learning as discussed in the episode MLOps.community #10 - MLOps - The Blind Men and the Elephant with Saurav Chakravorty and the clip Streamlining ML Processes?