Remove 2012 Remove Azure Remove Data Preparation
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Why is Git Not the Best for ML Model Version Control

The MLOps Blog

Starting from AlexNet with 8 layers in 2012 to ResNet with 152 layers in 2015 – the deep neural networks have become deeper with time. It requires significant effort in terms of data preparation, exploration, processing, and experimentation, which involves trying out algorithms and hyperparameters.

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A review of purpose-built accelerators for financial services

AWS Machine Learning Blog

Around this time, industry observers reported NVIDIA’s strategy pivoting from its traditional gaming and graphics focus to moving into scientific computing and data analytics. in 2012 is now widely referred to as ML’s “Cambrian Explosion.” The union of advances in hardware and ML has led us to the current day. Work by Hinton et al.

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Introducing the DataRobot AI Cloud: A Closer Look

DataRobot

Since DataRobot was founded in 2012, we’ve been committed to democratizing access to the power of AI. We’re building a platform for all users: data scientists, analytics experts, business users, and IT. Let’s dive into each of these areas and talk about how we’re delivering the DataRobot AI Cloud Platform with our 7.2

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