Ben Wilson Michael Berk Podcasts

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. Sponsor…

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. Sponsors Chuck's Resume Template Developer Book Club starting Become a Top 1% Dev with a Top End Devs Membership Advertising Inquiries: ht…

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. Sponsors Chuck's Resume Template Developer Book Club starting Become a Top 1% Dev with a Top End Devs Membership Links LinkedIn: Ruslan Khamidullin …

"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 ML General Artificial Intelligence Some personal opinions about the overlap between "the divine" and AI Sponsors Chuck's Resume Tem…

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. Sponsors Chuck's Resume Template Developer Book Club starting Become a Top 1% Dev with a Top End Devs Me…

By Ben Wilson, Michael Berk

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. Sponsors Chuck's Resume Template Developer Book Club starting Become a Top 1% Dev wit…

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! Sponsors Chuck's Resume Template Developer Book Club starting with Clean Architecture by Robert C. Martin Become a Top 1% Dev with a Top End Dev…

Have you ever wondered about the most promising industries in Machine Learning? Today we will learn from Avi Goldfarb, the chair of AI at the University of Toronto, about... The most promising AI industries Potential problems with powerful AI The economics behind innovation On YouTube The Disruptive Power of Artificial Intelligence - ML 100 Sponsor…

In this episode, Ben talks with Rosaria Silipo, a Software Engineer and Developer Relations advocate at Knime. They discuss the benefits of low-code ML, delve into the history of ML development work as it has changed over the past few decades, and discuss a few stories about the importance of pursuing simplicity in implementations. On YouTube A His…

In this week's episode we meet with Mike Arov, committer to the MLOps tool framework lineapy. From the benefits of notebooks as development tooling for Data Science work to the complex refactoring needed to convert them to production-capable code bases, our conversation dives deep into the generally under-represented bridge tooling of code base con…

Let's be honest. We've all copied and pasted code from the internet. There are many great code sources and in this episode, Ben and Michael discuss how to leverage existing code. They explain how to understand a code base and some best practices for contribution. Sponsors Chuck's Resume Template Developer Book Club starting with Clean Architecture …

Corey Zumar talks about the new release of MLflow, 2.0, and what the new major features that are included in the release. Bilal and Corey then discuss managing feature implementation priorities, and selling large-scale project ideas to internal customers, end-users, executives, and the dev team. The discussion also centers around generalizing featu…

Get the Black Friday/Cyber Monday "Focus Blocks Bundle" Deal Coupon Code: "THRIVE" for a GIANT discount Are you looking at all the layoffs and uncertainty going on and wondering if your company is the next to cut back? Or, maybe you're a freelancer or entrepreneur who is trying to figure out how to deliver more value to gain or retain customers? Ma…

Do you multitask? If so, you'll want to check out this episode. We'll cover... The difference between good and bad context switching Some personal stories about context switching on projects Practical tips you can leverage to improve your productivity Sponsors Chuck's Resume Template Developer Book Club starting with Clean Architecture by Robert C.…

Have you ever wondered how to prioritize your ML projects? Today we will talk about... The difference between applied ML and ML frameworks How to effectively scope projects via Heilmeier's Catechism Sponsors Chuck's Resume Template Developer Book Club starting with Clean Architecture by Robert C. Martin Become a Top 1% Dev with a Top End Devs Membe…

Have you ever wondered how to efficiently learn topics? In this episode, we discuss how to conduct a research spike within an ML team setting. Sponsors Chuck's Resume Template Developer Book Club starting with Clean Architecture by Robert C. Martin Become a Top 1% Dev with a Top End Devs Membership Advertising Inquiries: https://redcircle.com/brand…

Have you ever wondered why data science is hard? Well, in this episode we cover some common data science challenges and how the founders of DagsHub are looking to solve them. Sponsors Top End Devs Coaching | Top End Devs Links Dean Pleban Advertising Inquiries: https://redcircle.com/brands Privacy & Opt-Out: https://redcircle.com/privacy…

In this show, we cover some practical tips for writing reliable ML code. Here are some of the questions we look to answer... What are tests and why should you use them? What's the difference between unit tests and integration tests? What should you test? How should you write tests in python? (the answer is to use pytest) Sponsors Top End Devs Coach…

Charles Simon, BSEE, MSCs is a nationally recognized entrepreneur and software developer who has many years of computer experience in industry including pioneering work in artificial intelligence (AI). Mr. Simon's technical experience includes the creation of two unique AI systems along with software for successful neurological test equipment combi…

Fernando Lopez joins the show today to share his ML insights with a video interview recruiting platform for candidate hiring. Michael and Ben also deep dive into various related ML models and AI topics. In this episode… Core software engineering skills Practice data algorithms and structures Working towards production-grade ML Data engineering and …

Today the panel discusses high level distributed time series models, using a hot dog stand company as the case study to anchor the understanding with these models. In this episode… Understanding use case ML flow models and events KPI forecasts Metadata outputs Prediction intervals for hotdog data Automated time series forecasts Libraries required f…

Today on the show, the panel discusses time series models, practical tips and tricks, and shares stories and examples of various models and the processes for optimal application in your ML workflows. In this episode… Ben’s time series model for sales forecasting The flat line model Examples using time series models Understanding your data Lag funct…

Optical character recognition, or OCR for short, is used to describe algorithms and techniques (both electronic and mechanical) to convert images of text to machine-encoded text. Today on the show, Ahmad Anis shares how he applies Machine Learning to OCR for small hardware applications, for example, blurring a face in a video in real time or on a s…

Award winning data evangelist, AI strategist, and innovation leader Vidhi Chugh joins the show today to share her perspective on various topics, including data quality, AI innovation strategies, responsible AI, model intelligence, and much more! In this episode… The importance of innovation Glorified failure projects Responsible AI Data driven comp…

Enjoy this intellectually stimulating conversation with Michael Berk and guest on the show, Aliaksei Mikhailiuk, ML/AI engineer at Snapchat as they discuss everything AI computer graphics to techniques on striking the efficiency-accuracy trade-off for deep neural networks on constrained devices. In this episode… From academics to machine learning M…

Adam Ross Nelson helps current and aspiring data professionals enter and level up in the field by uncovering and showcasing their existing data-related talents. Today on the show, Michael interviews Adam to share his various strategies and approaches on how to become a data scientist or make advanced changes in the data science career path. In this…

Michael Berk interviews Ken Youens-Clark today to discuss various topics including bioinformatics and programming, plus his career progressions including jazz drumming, technical writing, programming, academia, writing books, and solutions engineering. In this episode… Writing tests and type annotations Project development lifecycle Grading program…

Data excellence is the foundation of better AI. Today on the show, Michael Berk interviews Edouard d’Archimbaud, co-founder of Kili Technology, a Training Data Platform that turns raw, unstructured data to high-quality training data, at scale. Enjoy this engaging conversation about building AI responsibly on a foundation of good data. In this episo…

Jesse Langford spent the first half of his career as a golf instructor before pivoting to software engineering. Today on the show, Ben interviews Jesse to learn why and how he made this pivot, plus relevant career advice for all developers. Specific topics include taking ownership of your work, being comfortable making mistakes, and how to stretch …

When developing ML models, defining and selecting the model architecture will be fundamental to ensure the best possible outcomes. Parameters that define the model architecture are referred to as hyperparameters and the process of searching for the ideal model architecture is referred to as hyperparameter tuning. Today on the show, Ben and Michael …

Enjoy this engaging AMA conversation with Michael Berk asking Ben Wilson various questions related to industry, strategy, and approaches in data science and ML engineering. In this episode… Why should people trust you? What will you lose by hearing about other people’s failures vs. personally failing to learn? How do you view the current industry? …

Ben and Michael interview Maciej Balawejder, a mechanical engineering student passionate about AI, ML, and robotics. As an active contributor on Medium.com, Maciej has already made significant contributions to the AI and ML communities. On the show, they discuss Maciej’s recent article about optimizers in Machine Learning, plus their personal philo…

After ensuring your data has surpassed the hyper parameter tuning phase, what is the next step in your EDA protocol? Today on the show, Ben and Michael continue the discussion on EDA methodology within Machine Learning and discuss linear regression with OLS, decision trees, and common visualization tools for data scientists. In this episode... Line…

EDA is primarily used in machine learning to see what data can reveal beyond the formal modeling or hypothesis testing task and provides a better understanding of data set variables and the relationships between them. It can also help determine if the statistical techniques you are considering for data analysis are appropriate. Today on the show, B…

MLlib is Apache Spark's scalable machine learning library. Today, Ben and Michael discuss the ease of use, performance, algorithms, and utilities included in this library and how to execute the best ML workflow with MLlib. In this episode... Why stick with Spark libraries vs. a single node operation? What algorithms are not in Spark Lib? What is th…

Apache Spark is a lightning-fast unified analytics engine for large-scale data processing and machine learning. In this episode, Ben and Michael unpack Spark by ping-ponging questions and answers, supplemented by various examples applicable to machine learning workflows. In this Episode… How does Spark work? What makes Apache Spark effective? Dot r…

Ben and Michael walk through two different cases studies relative to production ML infrastructure and recommendation engines. The first is about a free on-line tutoring service for underserved communities called “Learn to Be”, and the second centers around the online course provider “Coursera”. Ben and Michael set up the case studies with fundament…

Ben interviews Michael Griffiths, Director of Data Science at ASAPP, a company leveraging AI and ML to augment and automate human work, improve operational efficiencies and customer experiences, and ultimately empower people to be their best. Michael shares specific examples of how this can be done for human agent productivity within contact center…

AutoML (automated machine learning) has become a hot topic over the past few years. Abid Ali Awan joins the show to share his approach to AutoML, when and how to utilize it compared to classic approaches. Ben and Abid also discuss open-source vs. proprietary platforms. What is AutoML? Automated machine learning provides methods and processes to mak…

Video is considered the most complicated data to process and the volumes of video production are growing from day to day. Ben and Michael talk with Oleg and Anastasiya about how to leverage robotics and advanced cognitive computing-based video processing algorithms to automate the most routine parts of editing and post-production. Specifically, the…

Michael and Ben talk about how to pick extra projects to build up your resume and become recognized as more of an expert. They discuss the specific ways to contribute within the community and who to interact with to strengthen your resume if you're new. Sponsors Top End Devs Coaching | Top End Devs Sponsored By: Coaching | Top End Devs: Do you want…

Machine learning is getting bigger by the second, so it’s good to know how to leverage it. In this episode, Michael asks Ben hypothetical questions around how to effectively deploy machine learning in multiple fields, including the stock market. In This Episode 1) How to get started in the stock market without having gobs of hedge fund money 2) The…

What happens when you teach ML and data science to kids? You learn a whole lot, too. In this episode, Ben and Michael sit down with Kathryn, a prolific writer and author who simplifies advanced concepts for kids to foster their passion for science. “I just love how curious kids are. I really connect with the questions they ask and how curious they …

Even an amazing algorithm can’t fix communication problems. In this episode, Ben and Michael sit down with Joe Reis, a data scientist and ML developer who’s passionate about helping people level up their communication and build solid business infrastructure. “I feel like the infrastructure piece is getting better. Once you get past the technical la…

Ever feel like you can’t see the forest through the trees? We get it. In this episode, Michael sits down with Maria Zentsova, an ML developer and data analyst who teaches us how to get a handle on our data. “We all know that more data leads to more accuracy, so it’s important to get hands on.” - Maria Zentsova In This Episode 1) What KDNuggets is m…

In this episode, Ben and Michael cover more of Shreya Shankar’s deep dive into ML monitoring, including the biggest production challenges, what you NEED to know about adversarial attacks, and how to conduct effective tests and never make past mistakes again. In This Episode 1) The BIGGEST production challenges when it comes to ML in 2022 2) What yo…

If you’re feeling a little nervous about your baby leaving the nest, we get it. In this episode, Ben and Daniel talk with Abhilash Pattnaik, where they discuss the ONE fact about ML you can’t forget, the do’s and don’ts about applying alerts, and the often-forgotten truth about data drift. “Machine learning models are not static; they are dynamic.”…

Ready to dive DEEP into predictive modeling? You’ve come to the right podcast. In this episode, Ben and Michael sit down with Maarit Widmann, a data scientist whose bread and butter is making models more accurate. They discuss how to effectively use confusion matrices and other tools, why you need to avoid THIS misconception to get accurate churn r…

Mo’ advancements mean mo’ problems, and today, Michael and Ben are diving into the biggest issues of ML monitoring in 2022. They lay out the ELEVEN (cause nothing good comes easy) potential pitfalls that you should know this year, the important questions that you NEED to ask yourself before launching your baby, and this ONE phenomenon that reveals …