Data Science and Analytics

How to choose MLOps tools (MLOps from first principles)

   ​ Understand the role of each tool to design and deploy robust ML pipelines that drive business impact and foster innovation.​ ​ If you are a Marvel fan, you might know that killing Thanos does not guarantee a safer world as there are other villains to deal with. Source: https://in.mashable.com/entertainment/24645/every-marvel-movie-villain-ranked Similarly, while building any machine …

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🍪 Machine Learning in the cookie-less era with Uri Goren

   ​ Dean talks with Uri Goren about the future of digital ads without cookies. They discuss challenges in personalization while maintaining privacy and explore new methods like probabilistic models and contextual features.​ ​ In this episode, Dean chats with Uri Goren, founder and CEO of Argmax, about Machine Learning and the future of digital advertising …

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Top Computer Vision Generative Models in 2024

   ​ Explore the top computer vision generative models of 2024 with our in-depth guide and improve team productivity and efficiency.​ ​ Intro Welcome to the comprehensive guide on the top computer vision generative models of 2024. As businesses continue to harness the power of generative AI, the impact on productivity and efficiency is undeniable, with …

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7 Best Machine Learning Workflow and Pipeline Orchestration Tools 2024

   ​ Explore the top ML workflow and pipeline tools, including tools from Netflix, to enhance your data science projects’ efficiency and impact.​ ​Image generated with Midjourney In today’s fast-paced world of data science, building impactful machine learning models relies on much more than selecting the best algorithm for the job. Data scientists and machine learning …

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A Scalable Google Drive Alternative for ML – Launching DagsHub Storage Buckets with Colab Integration

   ​ DagsHub launches Storage Buckets, integrating S3-Compatible, ML-focused storage with Google Colab for scalable data management in large-scale ML projects. Simplify your ML development cycle with our easy-to-use solution.​ ​[[{“value”:” TL;DR We’re launching DagsHub Storage Buckets – An S3-Compatible, easy to use, and ML focused storage – which is integrated with Google Colab for easy and scalable …

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How to Train a Custom LLM Embedding Model

   ​ Discover training custom LLM embeddings: Unlock embedding significance, fine-tuning strategies, and practical examples for NLP enhancements.​ ​[[{“value”:” Introduction Large language models (LLMs) such as GPT-3.5 and others like Gemini, Claude, and Mistral have paved in our regular everyday lives augmenting our productivity and enhancing our cognitive abilities. These models empower us to enhance creativity, …

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StyleTTS2: A Quest To Improve Zero-Shot Performance

   ​ Discover StyleTTS2’s breakthrough in text-to-speech technology: an innovative architecture that captures the essence of any voice with a brief reference. This blog delves into our journey enhancing zero-shot performance, tackling dataset challenges, and pushing the boundaries of TTS with StyleTTS2.​ ​[[{“value”:” Introduction Text-to-speech (TTS) technology is an ever-improving field, with every year seeing new …

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How to Evaluate Generative Image Models

   ​ Discover the revolution in AI image generation, from GANs to diffusion models, and the complexities of evaluating their innovative capabilities.​ ​ A Journey through the Evolution of Artificial Image Creation Aren’t you impressed at how easy it is to generate stunning artificial images nowadays? It’s truly incredible! However, evaluating the quality of these produced …

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How to Build a Full MLOps Solution For Computer Vision Using OSS

   ​ This guide will walk you through the key stages of building a robust MLOps pipeline, from data collection to model deployment, using popular open-source software (OSS) platforms.​ ​[[{“value”:” AI has been serving as the forefront for modern software engineering. Therefore, it’s important to efficiently develop, deploy, and maintain a machine learning model. To do …

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Healthcare Data Management with Dagshub: A Game-Changer for Forcura

   ​ Key MetricsAnnotation Time Reduction: Reduced document annotation time by 75%.Compliance Achievement Speed: Reached full AI policy compliance within 4 weeks.Operational Speed: Accelerated data processing pipeline, achieving a 50% increase in data processing speed.“Dagshub has revolutionized Forcura’s ability to manage and extract data that ultimately benefits​ ​ Key Metrics Annotation Time Reduction: Reduced document annotation …

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