Welcome to the Machine Learning Hub, your one-stop destination for all things related to machine learning!
Get ready to embark on an exciting journey into the realm of AI and discover how machines can learn and make intelligent decisions. Our blog articles are crafted with simplicity and clarity in mind, making complex machine learning concepts easy to understand for everyone. Whether you’re a beginner or an experienced practitioner, we’ve got you covered with informative and insightful content. Explore the fascinating world of algorithms, models, and data as we delve into supervised and unsupervised learning, reinforcement learning, and more. Discover practical applications in various domains like healthcare, finance, and autonomous vehicles. From introductory guides to advanced techniques, we’re here to help you demystify machine learning and unlock its potential. Join us on this journey as we unravel the secrets of machine learning and empower you to build intelligent systems that can analyze data, make predictions, and drive innovation.
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Why build things the hard way when you can design them the smart way? As a Supply Chain Data Scientist, I’ve explored various frameworks like LangChain and LangGraph to build AI agents using Python. Leveraging LLMs with LangChain for Supply Chain Analytics — A Control Tower Powered by GPT — (Image by Samir Saci) The illustration above is from an …
Automate Supply Chain Analytics Workflows with AI Agents using n8n Read More »
Today we’re introducing Gemini 2.5, our most intelligent AI model. Our first 2.5 release is an experimental version of 2.5 Pro, which is state-of-the-art on a wide range of benchmarks and debuts at #1 on LMArena by a significant margin. Gemini 2.5 models are thinking models, capable of reasoning through their thoughts before responding, resulting …
0. Least Squares is used almost everywhere when it comes to numerical optimization and regression tasks in machine learning. It aims at minimizing the Mean Squared Error (MSE) of a given model. Both L1 (sum of absolute values) and L2 (sum of squares) norms offer an intuitive way to sum signed errors while preventing them …
Least Squares: Where Convenience Meets Optimality Read More »
Notes References [1] John M Jumper, Richard Evans, Alexander Pritzel, Tim Green, Michael Figurnov, Olaf Ron-neberger, Kathryn Tunyasuvunakool, Russ Bates, Augustin Zídek, Anna Potapenko, Alex Bridgland, Clemens Meyer, Simon A A Kohl, Andy Ballard, Andrew Cowie, Bernardino Romera-Paredes, Stanislav Nikolov, Rishub Jain, Jonas Adler, Trevor Back, Stig Petersen, David A. Reiman, Ellen Clancy, Michal Zielinski, …
Benchmarking the next generation of never-ending learners Read More »
previous article on organizing for AI (link), we looked at how the interplay between three key dimensions — ownership of outcomes, outsourcing of staff, and the geographical proximity of team members — can yield a variety of organizational archetypes for implementing strategic AI initiatives, each implying a different twist to the product operating model. Now …
Evolving Product Operating Models in the Age of AI Read More »
Notes [1] Abramson, J., Ahuja, A., Barr, I., Brussee, A., Carnevale, F., Cassin, M., Chhaparia, R., Clark, S., Damoc, B., Dudzik, A. and Georgiev, P., 2020. Imitating interactive intelligence. arXiv preprint arXiv:2012.05672. [2] Abramson, J., Ahuja, A., Brussee, A., Carnevale, F., Cassin, M., Fischer, F., Georgiev, P., Goldin, A., Harley, T. and Hill, F., 2021. …
Building interactive agents in video game worlds Read More »
With the new age of problem-solving augmented by Large Language Models (LLMs), only a handful of problems remain that have subpar solutions. Most classification problems (at a PoC level) can be solved by leveraging LLMs at 70–90% Precision/F1 with just good prompt engineering techniques, as well as adaptive in-context-learning (ICL) examples. What happens when you …
R.E.D.: Scaling Text Classification with Expert Delegation Read More »
Advancing best-in-class large models, compute-optimal RL agents, and more transparent, ethical, and fair AI systems The thirty-sixth International Conference on Neural Information Processing Systems (NeurIPS 2022) is taking place from 28 November – 9 December 2022, as a hybrid event, based in New Orleans, USA. NeurIPS is the world’s largest conference in artificial intelligence (AI) …
Research Published 1 December 2022 Authors Julien Perolat, Bart De Vylder, Daniel Hennes, Eugene Tarassov, Florian Strub and Karl Tuyls DeepNash learns to play Stratego from scratch by combining game theory and model-free deep RL Game-playing artificial intelligence (AI) systems have advanced to a new frontier. Stratego, the classic board game that’s more complex than …
Mastering Stratego, the classic game of imperfect information Read More »
Research Published 6 December 2022 Authors Yoram Bachrach, János Kramár Agents cooperate better by communicating and negotiating, and sanctioning broken promises helps keep them honest Successful communication and cooperation have been crucial for helping societies advance throughout history. The closed environments of board games can serve as a sandbox for modelling and investigating interaction and …
