Jesse Anderson’s Post

If you want to access private sector data, or you are responsible for making that data available, this is the episode for you. In this podcast, our panel of experts from Hewlett Packard Enterprise and GitHub will give their practical tips for data scientists, practitioners, and research and innovation teams. https://hubs.li/Q02GWLY50

A few months ago, I had the opportunity to speak with 🎙Bart Farrell from KubeFM at ☸️ Kubecon Paris 🇫🇷. It was a short but engaging and a fun experience where we delved deep into the world of cloud-native observability and strategic metric management. 🔍 Some of the topics we touched on: • Managing Metrics in Kubernetes • Entity-centric observability • Bridging the AI-Kubernetes Knowledge Gap A big thank you to Bart and the KubeFM team, as well as Elastic, for the opportunity to share my thoughts. 📻 Keep tuning your FM dials as I hope to repeat this soon! #Kubernetes #Observability #GenAI #Podcast

Decision-making is an essential part of everyday life and one of the main applications of data science is making the decision-making process easier. However, mostly when data scientists build models, it’s to make a single decision. But in real life, decision-making is rarely that simple. In the latest episode of "Value Driven Data Science", I'm joined by Prof Warren Powell, Chief Innovation Officer at Optimal Dynamics, to discuss one way in which the decision-making process can become more complicated, in the form of sequential decision problems. Some of the things we discuss in this episode include: ✴ What is a sequential decision problem? ✴ Real-life examples of sequential decision problems and the disciplines in which they occur. ✴ The four main classes of techniques for solving sequential decision problems. ✴ How Warren's approach to addressing sequential decision problems differs from the standard approach in this space. ✴ The challenges of implementing sequential decision analysis techniques in practice. You can listen to this episode at the link below, or find it on Apple Podcasts, Amazon Music, Spotify or Google Podcasts. https://lnkd.in/giJzY-XV #datascience #podcast #ValueDrivenDataScience

Tuning in. We're celebrating 5 years of the STO Building Group podcast, #BuildingConversations. There have been so many great conversations with industry leaders, and many more to come. Tune in and take a listen! To get you started, here's an episode all about today's Mission Critical market and how we're navigating its myriad of challenges. We hope you enjoy! https://lnkd.in/eUhBEXZN #missioncritical #podcastanniversary #STOMissionCritical

🎙️ Google’s E-E-A-T & The Myth Of The Perfect Ranking Signal In a recent episode of Google’s Search Off The Record podcast, Search Director & Product Manager Elizabeth Tucker delves into E-E-A-T's role in search rankings. The key takeaway? Focus on quality content that demonstrates expertise and builds trust, rather than chasing a mythical E-E-A-T score. Full Podcast Link: https://lnkd.in/gbTHJXhM #SEO #google #EEAT #contentquality #rankingsignals #searchrankings

David Smith was interviewed by Jake Villarreal on the Match Relevant podcast. MLtwist focuses on helping companies that are working on releasing AI products by taking care of data preparation challenges for them. How does that work ? Our no code platform takes care of the data prep and will let you focus on training your model. You want to know more? Check out the interview 👇 #unstructureddata #AIdata #dataquality #datapipeline #datalabeling #datacleaning #datatransformation

Insightful discussion about the role of knowledge graphs in improving LLMs performance

The latest episode of the Data Engineering Podcast is available now! Episode 436 is ready to listen to and share with all of your friends and colleagues.

#MLtwist CEO David Smith sat down and discussed with Jake Villarreal on the Match Relevant podcast about MLtwist's mission, story and vision. Check it out to understand better the problems we are tackling, how we solve AI data pipeline challenges and allow all our customers to get high quality AI data at scale with our no code solution. #unstructureddata #AIdata #dataquality #datapipeline #datalabeling #datacleaning #datatransformation #AI

In episode two of our three-part series, explore the energy industry’s data transformation. Learn how companies build specialized teams, empower people with new data skills, and foster robust data cultures to drive actionable insights.