Use PyTorch Deep Learning Models with scikit-learn

The most popular deep learning libraries in Python for research and development are TensorFlow/Keras and PyTorch, due to their simplicity. The scikit-learn library, however, is the most popular library for general machine learning in Python. In this post, you will discover how to use deep learning models from PyTorch with the scikit-learn library in Python. …

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Enabling Responsible AI in Palantir Foundry

Editors Note: The following is a collaboration between authors from Palantir’s Product Development and Privacy & Civil Liberties (PCL) teams. It outlines how our latest model management capabilities incorporate the principles of responsible artificial intelligence so that Palantir Foundry users can effectively solve their most challenging problems. At Palantir, we’re proud to build mission-critical software …

3 key reasons why your organization needs Responsible AI

Responsibility is a learned behavior. Over time we connect the dots, understanding the need to meet societal expectations, comply with rules and laws, and to respect the rights of others. We see the link between responsibility, accountability and subsequent rewards. When we act responsibly, the rewards are positive; when we don’t, we can face negative …

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Unsupervised and semi-supervised anomaly detection with data-centric ML

Posted by Jinsung Yoon and Sercan O. Arik, Research Scientists, Google Research, Cloud AI Team Anomaly detection (AD), the task of distinguishing anomalies from normal data, plays a vital role in many real-world applications, such as detecting faulty products from vision sensors in manufacturing, fraudulent behaviors in financial transactions, or network security threats. Depending on …

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Optimize your machine learning deployments with auto scaling on Amazon SageMaker

Machine learning (ML) has become ubiquitous. Our customers are employing ML in every aspect of their business, including the products and services they build, and for drawing insights about their customers. To build an ML-based application, you have to first build the ML model that serves your business requirement. Building ML models involves preparing the …