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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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Learn what the Functional API is, and how to build complex keras models using it Photo by Hunter Harritt on Unsplash TensorFlow’s Sequential API helps the user to stack layers one on top of another, easily creating linear models, where the input of each layer is always the output of the previous one. But what …
Introduction to TensorFlow’s Functional API | by Javier Martínez Ojeda | Dec, 2024 Read More »
Responsibility & Safety Published 17 December 2024 Authors FACTS team Our comprehensive benchmark and online leaderboard offer a much-needed measure of how accurately LLMs ground their responses in provided source material and avoid hallucinations Large language models (LLMs) are transforming how we access information, yet their grip on factual accuracy remains imperfect. They can “hallucinate” …
FACTS Grounding: A new benchmark for evaluating the factuality of large language models Read More »
Let’s dive into the most important libraries in R and Python to visualise data and create different charts, and what the pros and cons are Being a pro in certain programming languages is the goal of every aspiring data professional. Reaching a certain level in one of the countless languages is a critical milestone for …
Research Published 3 May 2024 Developing next-gen AI agents, exploring new modalities, and pioneering foundational learning Next week, AI researchers from around the globe will converge at the 12th International Conference on Learning Representations (ICLR), set to take place May 7-11 in Vienna, Austria. Raia Hadsell, Vice President of Research at Google DeepMind, will deliver …
An aggregated look on the differences between then & now: 2020 vs 2024 — some big frustrations and positive learnings. Yes this is actually a screenshot of my own LinkedIn [1]. Introduction Application Process Interview Process Summary References This article is intended for data scientists looking for a company change, people considering applying and interviewing …
How Have Data Science Interviews Changed Over 4 Years? | by Matt Przybyla | Dec, 2024 Read More »
Update November 11, 2024: As of November 2024, we have released AlphaFold 3 model code and weights for academic use to help advance research. Learn more about AlphaFold tools. Original post: Inside every plant, animal and human cell are billions of molecular machines. They’re made up of proteins, DNA and other molecules, but no single …
Google DeepMind and Isomorphic Labs introduce AlphaFold 3 AI model Read More »
In this article we will explore why 128K tokens (and more) models can’t fully replace using RAG. We’ll start with a brief reminder of the problems that can be solved with RAG, before looking at the improvements in LLMs and their impact on the need to use RAG. Illustration by the author. RAG isn’t really …
A note from Google and Alphabet CEO Sundar Pichai: Information is at the core of human progress. It’s why we’ve focused for more than 26 years on our mission to organize the world’s information and make it accessible and useful. And it’s why we continue to push the frontiers of AI to organize that information …
Part 1: Leverage linear regression and decision trees to impute time-series gaps. Source: DALL-E. Missing data in time-series analysis — sounds familiar? Does missing data in your datasets due to malfunctioning sensors, transmission, or any kind of maintenance sound all too familiar to you? Well, missing values derail your forecast and skew your analysis. So, …
Missing Data in Time-Series: Machine Learning Techniques | by Sara Nóbrega | Dec, 2024 Read More »
Acknowledgements Genie 2 was led by Jack Parker-Holder with technical leadership by Stephen Spencer, with key contributions from Philip Ball, Jake Bruce, Vibhavari Dasagi, Kristian Holsheimer, Christos Kaplanis, Alexandre Moufarek, Guy Scully, Jeremy Shar, Jimmy Shi and Jessica Yung, and contributions from Michael Dennis, Sultan Kenjeyev and Shangbang Long. Yusuf Aytar, Jeff Clune, Sander Dieleman, …
