Google I/O 2019 | Cloud TPU Pods: AI Supercomputing for Large Machine Learning Problems Cloud Tensor Processing Unit (TPU) is an ASIC designed by Google for neural network processing. TPUs feature a domain specific architecture designed specifically for accelerating TensorFlow training and prediction workloads and provides performance benefits on machine learning production use. Learn the …

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The human race has long designed and used tools to help us solve problems, from flint axes to space shuttles. They affect our lives and shape society in expected and sometimes unexpected ways. We may understand how these tools work – after all, we built them – but sometimes it’s the use they’re put to …

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Elon Musk grabbed a lot of attention with his July 16 announcement that his company Neuralink plans to implant electrodes into the brains of people with paralysis by next year. Their first goal is to create assistive technology to help people who can’t move or are unable to communicate. If you haven’t been paying attention, …

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Machine learning and artificial intelligence (AI) are some of the hottest buzzwords around, especially in the open source community. It seems that every month brings a new machine learning system, each focused on a different application. The good news is that since academics developed many of these frameworks, they are often open source by default. Even …

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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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Arguably one of the most important skills you must have in order to get started with using statistical methods is knowing the scale or level of measurement of your data. The appropriate method of analysis for your data is dependent on the scale  it was measured in. Here’s a quick rundown of the four levels …

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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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The normal distribution is arguably the most used distribution in statistics. A lot of statistical methods rely on assuming that your data is normally distributed.  What is so special about it? The infamous bell The normal distribution is characterized by its trademark bell-shaped curve. The shape of the bell curve is dictated by two parameters. …

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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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