Explore the future of collaborative ML workflows in this engaging episode with Dr. Greg Michaelson, Co-Founder of Zerve. Dr. Michaelson introduces the groundbreaking Zerve IDE and Pypelines project, addressing the critical gap in AutoML for commercial use and pinpointing why many A.I. projects don't meet their objectives. Gain insights into steering AI initiatives towards success and enhancing project communication, all in this insightful session.

This episode is brought to you by Oracle NetSuite business software (https://netsuite.com/superdata), and by Prophets of AI (https://prophetsofai.com), the leading agency for AI experts. Interested in sponsoring a SuperDataScience Podcast episode? Visit https://passionfroot.me/superdatascience for sponsorship information.

In this episode you will learn:
• Why Zerve IDE is so sorely needed [04:50]
• Pypelines: AutoML open-source in python [30:00]
• Why most commercial A.I. projects fail and how to ensure they succeed [47:45]
• How AutoML will impact the role of the data scientist [53:21]
• Greg's background as a pastor and working at DataRobot [1:03:40]
• How to develop impressive communication and storytelling skills [1:16:16]

Additional materials: www.superdatascience.com/753

The Super Data Science Podcast: Machine Learning | AI | Success

753: Blend Any Programming Languages in Your ML Workflows, with Dr. Greg Michaelson

Welcome back to *AI with Shaily,* hosted by Shailendra Kumar, a lively and insightful show that brings you the latest and greatest in artificial intelligence with a personal touch! 🎙️🤖 Today’s episode dives deep into how Large Language Models (LLMs), like GPT, are revolutionizing traditional machine learning workflows in exciting new ways.

Shailendra uses a tasty cooking analogy 🍳 to explain the transformation: imagine you’ve always prepared every ingredient yourself, but now you have a smart kitchen assistant who not only helps prep but suggests new spices you never considered. That’s exactly what LLMs are doing for feature engineering — automating and enhancing the process of extracting meaningful features from complex data like text and images. This upgrade is like swapping a butter knife for a chef’s knife — sharper, more efficient, and precise. 🔪✨

The episode also highlights a hot topic buzzing on LinkedIn and Twitter: the merging of MLOps (machine learning operations) and LLMOps (operations focused on large language models). Teams are creating hybrid systems where traditional ML algorithms and LLMs coexist, deployed and monitored seamlessly. Frameworks like LangChain are gaining popularity, helping move projects from prototype to production at lightning speed. ⚙️🚀 Shailendra shares his excitement about this convergence, comparing it to his first experience automating an ML deployment — only now on a much grander scale!

Another fascinating point is how LLMs are not just analyzing data but actively augmenting the training process itself. They can generate synthetic data, provide feedback, and identify the most important samples to improve dataset quality — acting like a coach who trains and scouts the best plays on the field. 🏈📊 Plus, hybrid inference pipelines are emerging, where LLMs handle unstructured text with their natural language skills, while traditional ML methods process structured data. This combo is especially powerful in sensitive fields like healthcare and finance, where both numerical accuracy and subtle context matter deeply. 💉💰

Importantly, Shailendra emphasizes the growing trend of bringing humans back into the AI loop. This blend of AI power and human judgment ensures trustworthy, explainable outcomes. Imagine an LLM flagging a tricky prediction for a human expert’s review or generating simple explanations so users aren’t lost in technical jargon. It’s a perfect balance of machine efficiency and human insight — a crucial step toward responsible AI. 🤝🧠

Before signing off, Shailendra shares a valuable pro tip: invest time in prompt engineering tailored to your specific datasets. Fine-tuning the questions you ask LLMs can dramatically boost feature quality and overall model performance. It’s like the secret seasoning that turns a good dish into a wow-worthy meal! 🌶️✨

He leaves listeners with a thought-provoking question: How ready are you to blend these powerful language models into your existing ML setups? Are you prepared to let AI be your sous-chef in the data kitchen? 🍽️🤔

To inspire, Shailendra quotes AI pioneer Andrew Ng: “AI is the new electricity,” reminding us that this powerful force is now being wired directly into the data pipelines fueling our systems. ⚡🔌

Don’t miss out on more episodes of *AI with Shaily* available on YouTube, Twitter, LinkedIn, and Medium. Subscribe for your weekly dose of AI breakthroughs and share your thoughts to keep the conversation vibrant and exciting! 🌐📲

Till next time, keep experimenting, questioning, and AI-ing smartly! This is Shailendra Kumar signing off from *AI with Shaily.* 🎧🤓✨

LLMs as Your AI Sous-Chef: Revolutionizing Machine Learning Workflows with Hybrid Intelligence

Unlock the secrets of data mastery with Shailendra, a 27-year veteran in AI, ML, and Data Science, driving AU$ 6 Billion in transformative value. As the author of 'Making Money out of Data,' their strategies redefine digital success. With expertise honed at IBM and Accenture, they drive innovation and data monetization. Explore how loyalty programs like Flybuys and Everyday Rewards revolutionize business—connect with Shaily today.

The latest machine learning, A.I., and data career topics from across both academia and industry are brought to you by host Dr. Jon Krohn on the Super Data Science Podcast.

As the quantity of data on our planet doubles every couple of years and with this trend set to continue for decades to come, there's an unprecedented opportunity for you to make a meaningful impact in your lifetime. In conversation with the biggest names in the data science industry, Jon cuts through hype to fuel that professional impact.

Whether you're curious about getting started in a data career or you're a deep technical expert, whether you'd like to understand what A.I. is or you'd like to integrate more data-driven processes into your business, we have inspiring guests and lighthearted conversation for you to enjoy.

We cover tools, techniques, and implementation tricks across data collection, databases, analytics, predictive modeling, visualization, software engineering, real-world applications, commercialization, and entrepreneurship − everything you need to crush it with data science.

New tracks tagged #ML workflows