Posts in category

Machine Learning


Our use of Artificial Intelligence is growing along with advancements in the field. It has gone to the point that it is used in riskier areas such as hiring, criminal justice, and healthcare. This is with the hope the AI will provide less biased results compared to humans. In their paper, Jake Silberg and James …

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PyCon 2019 | Scikit-learn, wrapping your head around machine learning Speaker: Chalmer Lowe   A gentle introduction to machine learning through scikit-learn. This tutorial will enable attendees to understand the capabilities and limitations of machine learning through hands-on code examples and fun and interesting datasets. Learn when to turn to machine learning and which tools …

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PyCon 2019 | Pandas Is For Everyone Speaker: Daniel Chen   Data Science and Machine learning have been synonymous with languages like Python. Libraries like Numpy and Pandas have become the de facto standard when working with data. The DataFrame object provided by Pandas gives us the ability to work with heterogeneous unstructured data that …

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Google I/O 2019 | TF-Agents: A Flexible Reinforcement Learning Library for TensorFlow TF-Agents is a clean, modular, and well-tested open-source library for Deep Reinforcement Learning with TensorFlow. This session will cover recent advancements in Deep RL, and show how TF-Agents can help to jump start your project. You will also see how TF-Agent library components …

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Google I/O 2019 | Machine Learning Fairness: Lessons Learned ML fairness is a critical consideration in machine learning development. This session will present a few lessons Google has learned through our products and research and how developers can apply these learnings in their own efforts. Techniques and resources will be presented that enable evaluation and …

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Artificial neural networks were created to imitate processes in our brains, and in many respects – such as performing the quick, complex calculations necessary to win strategic games such as chess and Go – they’ve already surpassed us. But if you’ve ever clicked through a CAPTCHA test online to prove you’re human, you know that …

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Google I/O 2019 | Federated Learning: Machine Learning on Decentralized Data Meet federated learning: a technology for training and evaluating machine learning models across a fleet of devices (e.g. Android phones), orchestrated by a central server, without sensitive training data leaving any user’s device. Learn how this privacy-preserving technology is deployed in production in Google …

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Deepfake videos are hard for untrained eyes to detect because they can be quite realistic. Whether used as personal weapons of revenge, to manipulate financial markets or to destabilize international relations, videos depicting people doing and saying things they never did or said are a fundamental threat to the longstanding idea that “seeing is believing.” …

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PyCon 2019 | Measuring Model Fairness Speaker: J. Henry Hinnefeld   When machine learning models make decisions that affect people’s lives, how can you be sure those decisions are fair? When you build a machine learning product, how can you be sure your product isn’t biased? What does it even mean for an algorithm to …

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PyCon 2019 | Introduction to Data Science with Python Speaker: Grishma Jena   Wish to perform Data Science but don’t know how to? Have a dataset that you really want to analyze but not sure how to start? This hands-on session teaches how to explore datasets, use Machine Learning algorithms and derive insights from models …

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