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The new NISS AI, Statistics & Data Science in Practice series launches today! Check out Prof. Bin Yu's talk on "Veridical Data Science: Bridging the Gap in Education and Research" moderated by NISS Affiliates Committee Chair Dr. Nancy J McMillan! Free, 10/15 11:30-1:00ET, register here: https://lnkd.in/emdurbjJ More About `AI, Data Science, and Statistics in Practice':   The NISS AI, Data Science, and Statistics in Practice is a monthly event series part of the NISS Collaboratory (CoLab) will bring together leading experts from industry and academia to discuss the latest advances and practical applications in AI, data science, and statistics. Each session will feature a keynote presentation on cutting-edge topics, where attendees can engage with speakers on the challenges and opportunities in applying these technologies in real-world scenarios. This series is intended for professionals, researchers, and students interested in the intersection of AI, data science, and statistics, offering insights into how these fields are shaping various industries. The series is designed to provide participants with exposure to and understanding of how modern data analytic methods are being applied in real-world scenarios across various industries, offering both theoretical insights, practical examples, and discussion of issues. Upcoming Featured Topics: Veridical Data Science Statistics and Experimentation Needs in Industry Generative AI for Use in Industry Causal AI in Finance and Technology Industries Uncertainty Quantification for Random Forests Deep Learning Methods for Closed-Loop Neuromodulation Machine Learning for Airborne Biological Hazard Detection Causal Inference in Marketing Analytics Practical Return on AI Investment

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Real-world AI use cases changing data engineering right now 👀 In the first of our chats with our Director of Data Science, Julian Wiffen, we dive into current use cases that are already having a significant impact on productivity. #AI #dataengineering

Here, Julian Wiffen begins to dive into how Matillion is using LLMs and RAG for one of our own internal use cases around improving support response times while simultaneously training the models to do more. 🔑 🔓 📈 #AI #dataengineering #LLM #RAG

Day #7 of Data Science & AI. Stepping into Gradient Descent using the first derivative of a cost function.

Great day at the Spatial Data Science conference 2024. Some very interesting innovation in LI from the data scientists! Particularly around generative AI capabilities. #SDSC2024 #generativeAI #LocationIntelligence

Talking to Cal Al-Dhubaib (Head of AI & Data Science at Further) about building trust in AI! Join us and ask questions :)

💡 Exploring the hurdles in generative AI adoption! Ilia Badeev, Data Science Lead from Trevolution Group shares insights with PYMNTS about the challenges and risks involved. Dive into the details: https://lnkd.in/gV_hsvhC

Solutions Review’s “InsightJam.com” (US) interviewed Imran Chaudhri as part of a panel discussion about the dynamic intersection of AI and graph databases and their combined potential to revolutionize data management and application development. Watch Now: https://lnkd.in/gyHnT3RZ #datamanagement #dataplatform #databases #AI

I've read 57 Books on AI and Data Science - these are the best (for 2025) #ai #datascience #bestbooks https://lnkd.in/eMcRcKrP