Evaluating and Building AI Systems - ML 166

Evaluating and Building AI Systems - ML 166

Michael Berk dives deep into the adventures of AI and machine learning with our special guest, Richmond Alake, a staff developer advocate at MongoDB. Richmond's journey from web development to AI was driven by a quest for excitement and new challenges. In this episode, he shares how he transitioned into the AI field, his passion for using writing as a learning tool, and the importance of continuous learning in evolving tech landscapes.


They explore the intricacies of building and evaluating Retrieval-Augmented Generation (RAG) systems, the benefits of MongoDB's versatile database functionalities, and the pressing challenges in machine learning data collection and evaluation. Richmond also gives us a peek into MongoDB's advanced solutions for AI application development and how strategic data chunking can impact efficiency.
Whether you're a budding AI enthusiast or an experienced developer looking to expand your horizons, this episode is packed with practical advice, career insights, and the latest trends in AI and machine learning. Stay tuned as we uncover how to navigate the complexity of RAG pipelines and the evolving landscape of generative AI. Let's get started!

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Where ML and DevOps Meet - ML 108

Where ML and DevOps Meet - ML 108

Hosts of the Adventures in DevOps podcast, Jillian Rowe and Jonathan Hall, join Ben and Michael on this week's episode crossover. They talk about the intersection of ML and DevOps. They dive into the concepts and differences between ML and DevOps. Additionally, they talk about how ML ideas may be applied to DevOps principles and vice versa.SponsorsChuck's Resume TemplateDeveloper Book Club startingBecome a Top 1% Dev with a Top End Devs MembershipAdvertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacyBecome a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support.

17 Maalis 20231h 5min

How Does ChatGPT Work? - ML 107

How Does ChatGPT Work? - ML 107

ChatGPT is the most robust free chatbot. It can answer questions, write code, and summarize text. Today we will talk about the creation of ChatGPT, its implications for society, and how the model actually works. SponsorsChuck's Resume TemplateDeveloper Book Club startingBecome a Top 1% Dev with a Top End Devs MembershipAdvertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacyBecome a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support.

10 Maalis 202348min

Machine Learning for Movie Scripts - ML 106

Machine Learning for Movie Scripts - ML 106

Today we look at an applied use case for ML: parsing movie scripts. Expect to learn about bringing ML to new industries, the future of Large Language Models (LLM), and automation in the movie industry.SponsorsChuck's Resume TemplateDeveloper Book Club startingBecome a Top 1% Dev with a Top End Devs MembershipLinksLinkedIn: Ruslan KhamidullinAdvertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacyBecome a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support.

3 Maalis 202345min

ChatGPT and the Divine - ML 105

ChatGPT and the Divine - ML 105

"Any sufficiently advanced technology is indistinguishable from magic." Today, Michael and Ben talk about the broad implications of ChatGPT and similar algorithms. Expect to learn about...The difference between AI and MLGeneral Artificial IntelligenceSome personal opinions about the overlap between "the divine" and AISponsorsChuck's Resume TemplateDeveloper Book Club startingBecome a Top 1% Dev with a Top End Devs MembershipAdvertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacyBecome a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support.

23 Helmi 202351min

Deep Learning for Tabular and Time Series Data - ML 104

Deep Learning for Tabular and Time Series Data - ML 104

Today we speak with a staff data scientist at Walmart who specializes in forecasting. He has built an open-source tool that allows you to leverage tabular data in PyTorch. He also has written a book on time series forecasting with deep learning.SponsorsChuck's Resume TemplateDeveloper Book Club startingBecome a Top 1% Dev with a Top End Devs MembershipLinks[2207.08548] GATE: Gated Additive Tree Ensemble for Tabular Classification and RegressionModern Time Series Forecasting with Python: Explore industry-ready time series forecasting using modern machine learning and deep learningLinkedIn: Manu JosephTwitter: @manujosephvGitHub: manujosephvAdvertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacyBecome a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support.

16 Helmi 20231h 8min

Notebooks vs. IDEs With Fabian Jakobs - ML 103

Notebooks vs. IDEs With Fabian Jakobs - ML 103

How do you develop ML code? Do you use notebooks or do you use IDEs? In this episode, we get some practical advice from both Ben and our guest on leveraging software principles to write better code in both an IDE and notebook environment. We'll also learn about a cool new Databricks feature that will help you run ML code from an IDE.SponsorsChuck's Resume TemplateDeveloper Book Club startingBecome a Top 1% Dev with a Top End Devs MembershipLinks Databricks extension for Visual Studio Code | Databricks on AWSLinkedIn: Fabian JakobsLinkedIn: DatabricksAdvertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacyBecome a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support.

9 Helmi 202345min

How to think about Optimization - ML 102

How to think about Optimization - ML 102

In this week's episode, we meet with Micheal McCourt, the head of engineering at SigOpt. He is an industry expert on optimization algorithms, so expect to learn about constraint-active search, SigOpt's new open-source optimizer, and how to run an engineering team.SponsorsChuck's Resume TemplateDeveloper Book Club startingBecome a Top 1% Dev with a Top End Devs MembershipLinksMichael McCourt | SigOptLinkedIn: Michael McCourtAdvertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacyBecome a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support.

3 Helmi 202350min

Protecting Your ML From Phishing And Hackers - ML 101

Protecting Your ML From Phishing And Hackers - ML 101

Have you ever wondered how to secure a cloud deployment? Well, today we talk to the president at a cloud security company about personal security, detecting malicious actors, startup trends, and much more!SponsorsChuck's Resume TemplateDeveloper Book Club starting with Clean Architecture by Robert C. MartinBecome a Top 1% Dev with a Top End Devs MembershipLinksLinkedIn: Kevin Dominik KorteTwitter: @KeDKorte Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacyBecome a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support.

27 Tammi 202341min

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