Machine Learning

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.

Let’s shape the future together with the power of machine learning!

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Building safer dialogue agents – Google DeepMind

Research Published 22 September 2022 Authors The Sparrow team Training an AI to communicate in a way that’s more helpful, correct, and harmless In recent years, large language models (LLMs) have achieved success at a range of tasks such as question answering, summarisation, and dialogue. Dialogue is a particularly interesting task because it features flexible …

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Building a Personal API for Your Data Projects with FastAPI

have you had a messy Jupyter Notebook filled with copy-pasted code just to re-use some data wrangling logic? Whether you do it for passion or for work, if you code a lot, then you’ve probably answered something like “way too many”. You’re not alone. Maybe you tried to share data with colleagues or plugging your …

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How AI can decipher dolphin communication

Sharing DolphinGemma with the research community Recognizing the value of collaboration in scientific discovery, we’re planning to share DolphinGemma as an open model this summer. While trained on Atlantic spotted dolphin sounds, we anticipate its potential utility for researchers studying other cetacean species, like bottlenose or spinner dolphins. Fine-tuning may be required for different species’ …

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When Physics Meets Finance: Using AI to Solve Black-Scholes

DISCLAIMER: This is not financial advice. I’m a PhD in Aerospace Engineering with a strong focus on Machine Learning: I’m not a financial advisor. This article is intended solely to demonstrate the power of Physics-Informed Neural Networks (PINNs) in a financial context. , I fell in love with Physics. The reason was simple yet powerful: …

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Load-Testing LLMs Using LLMPerf | Towards Data Science

Language Model (LLM) is not necessarily the final step in productionizing your Generative AI application. An often forgotten, yet crucial part of the MLOPs lifecycle is properly load testing your LLM and ensuring it is ready to withstand your expected production traffic. Load testing at a high level is the practice of testing your application …

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Try generating video in Gemini, powered by Veo 2

Starting today, Gemini Advanced users can generate and share videos using our state-of-the-art video model, Veo 2. In Gemini, you can now translate text-based prompts into dynamic videos. Google Labs is also making Veo 2 available through Whisk, a generative AI experiment that allows you to create new images using both text and image prompts, …

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Solving the mystery of how an ancient bird went extinct

AI provides a new tool for studying extinct species from 50,000 years ago Researchers Beatrice Demarchi from the University of Turin, Josefin Stiller from the University of Copenhagen, and Matthew Collins from the University of Cambridge and University of Copenhagen share their AlphaFold story. Could burn marks on ancient eggshells explain the disappearance of the …

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Learnings from a Machine Learning Engineer — Part 6: The Human Side

In my , I have spent a lot of time talking about the technical aspects of an Image Classification problem from data collection, model evaluation, performance optimization, and a detailed look at model training. These elements require a certain degree of in-depth expertise, and they (usually) have well-defined metrics and established processes that are within our control. Now it’s time to …

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