Andrew Trask

Andrew Trask

@OpenMinedOrg leader @DeepMind senior research scientist @UniofOxford phd student @UN privacy task team @Manning author @Udacity instructor

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4 Book Recommendations by Andrew Trask

  • Grokking Deep Learning

    Andrew W. Trask

    Summary Grokking Deep Learning teaches you to build deep learning neural networks from scratch! In his engaging style, seasoned deep learning expert Andrew Trask shows you the science under the hood, so you grok for yourself every detail of training neural networks. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Deep learning, a branch of artificial intelligence, teaches computers to learn by using neural networks, technology inspired by the human brain. Online text translation, self-driving cars, personalized product recommendations, and virtual voice assistants are just a few of the exciting modern advancements possible thanks to deep learning. About the Book Grokking Deep Learning teaches you to build deep learning neural networks from scratch! In his engaging style, seasoned deep learning expert Andrew Trask shows you the science under the hood, so you grok for yourself every detail of training neural networks. Using only Python and its math-supporting library, NumPy, you'll train your own neural networks to see and understand images, translate text into different languages, and even write like Shakespeare! When you're done, you'll be fully prepared to move on to mastering deep learning frameworks. What's inside The science behind deep learning Building and training your own neural networks Privacy concepts, including federated learning Tips for continuing your pursuit of deep learning About the Reader For readers with high school-level math and intermediate programming skills. About the Author Andrew Trask is a PhD student at Oxford University and a research scientist at DeepMind. Previously, Andrew was a researcher and analytics product manager at Digital Reasoning, where he trained the world's largest artificial neural network and helped guide the analytics roadmap for the Synthesys cognitive computing platform. Table of Contents Introducing deep learning: why you should learn it Fundamental concepts: how do machines learn? Introduction to neural prediction: forward propagation Introduction to neural learning: gradient descent Learning multiple weights at a time: generalizing gradient descent Building your first deep neural network: introduction to backpropagation How to picture neural networks: in your head and on paper Learning signal and ignoring noise:introduction to regularization and batching Modeling probabilities and nonlinearities: activation functions Neural learning about edges and corners: intro to convolutional neural networks Neural networks that understand language: king - man + woman == ? Neural networks that write like Shakespeare: recurrent layers for variable-length data Introducing automatic optimization: let's build a deep learning framework Learning to write like Shakespeare: long short-term memory Deep learning on unseen data: introducing federated learning Where to go from here: a brief guide

    @biobenkj Fwiw - I wrote a book which unpacks intuitions around embeddings, neural layers, etc. quite extensively (with lots of example code). https://t.co/t1VNTUXsk0

  • Privacy in Context

    Helen Nissenbaum

    Privacy is one of the most urgent issues associated with information technology and digital media. This book claims that what people really care about when they complain and protest that privacy has been violated is not the act of sharing information itself—most people understand that this is crucial to social life —but the inappropriate, improper sharing of information. Arguing that privacy concerns should not be limited solely to concern about control over personal information, Helen Nissenbaum counters that information ought to be distributed and protected according to norms governing distinct social contexts—whether it be workplace, health care, schools, or among family and friends. She warns that basic distinctions between public and private, informing many current privacy policies, in fact obscure more than they clarify. In truth, contemporary information systems should alarm us only when they function without regard for social norms and values, and thereby weaken the fabric of social life.

    Still one of the best books introducing the basics of (the maths of) Differential Privacy https://t.co/FeI0seLsM6

  • This book contains a framework for productive discussion and thinking about ethics and Big Data in business environments. With the increasing size and scope of information that Big Data technologies can provide business, maintaining an ethical practice benefits from a common framework of understanding and vocabulary for discussing questions about coherent and consistent practices. A framework provides you with a set of conceptual terms and tools that help decision-markers to engage difficult questions the expanding role Big Data plays in an increasing variety of products and services. The approach is to develop a set of terms and concepts, consider ethical principles useful in meaningful business discussions, and then explore and compare several overall views on data handling to help inform the development of an ethics-based data strategy. The focus is to enhance effective decision-making in business rather than legislate what ought to be done with data. In this book, you will learn methods and techniques to facilitate rigorous, productive internal discussion, and express coherent and consistent positions on your organization's perspective on the use of Big Data in commerce.

    Still one of the best books introducing the basics of (the maths of) Differential Privacy https://t.co/FeI0seLsM6

  • What Money Can't Buy

    Michael Sandel

    Should we pay children to read books or to get good grades? Is it ethical to pay people to test risky new drugs or to donate their organs? What about hiring mercenaries to fight our wars, outsourcing inmates to for-profit prisons, auctioning admission to elite universities, or selling citizenship to immigrants willing to pay? Isn't there something wrong with a world in which everything is for sale? In recent decades, market values have crowded out nonmarket norms in almost every aspect of life-medicine, education, government, law, art, sports, even family life and personal relations. Without quite realizing it, Sandel argues, we have drifted from having a market economy to being a market society. In What Money Can't Buy, Sandel examines one of the biggest ethical questions of our time and provokes a debate that's been missing in our market-driven age: What is the proper role of markets in a democratic society, and how can we protect the moral and civic goods that markets do not honour and money cannot buy?

    This is hands down the most interesting thing I've read in at least a month. Thanks for the DM @njwfish "What Money Can’t Buy: The Moral Limits of Markets" - Michael J. Sandel https://t.co/HDGyOu8rCo https://t.co/eVYsrZeqd3