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The author, a longtime artificial intelligence researcher specializing in natural-language processing, covers feed-forward neural nets, convolutional neural nets, word embeddings, recurrent neural nets, sequence-to-sequence learning, deep reinforcement learning, unsupervised models, and other fundamental concepts and techniques. Students and practitioners learn the basics of deep learning by working through programs in Tensorflow, an open-source machine learning framework. \"I find I learn computer science material best by sitting down and writing programs,\" the author writes, and the book reflects this approach.\u003c\/p\u003e \u003cp\u003eEach chapter includes a programming project, exercises, and references for further reading. An early chapter is devoted to Tensorflow and its interface with Python, the widely used programming language. 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Today's programmers in AI will find this volume's superior coverage of programming techniques and easily applicable style anything but common.","brand":"WoB","offers":[{"title":"US \/ GOOD \/ SBYB","offer_id":50298878001425,"sku":"CIN0898596092G","price":0.0,"currency_code":"GBP","in_stock":false},{"title":"GB \/ VERY_GOOD \/ INTERNAL","offer_id":50314561913105,"sku":"GOR010112673","price":0.0,"currency_code":"GBP","in_stock":true},{"title":"US \/ WELL_READ \/ SBYB","offer_id":50627544482065,"sku":"CIN0898596092A","price":0.0,"currency_code":"GBP","in_stock":false},{"title":"US \/ VERY_GOOD \/ SBYB","offer_id":50976440189201,"sku":"CIN0898596092VG","price":0.0,"currency_code":"GBP","in_stock":false},{"title":"GB \/ GOOD \/ INTERNAL","offer_id":53163031920913,"sku":"GOR005113817","price":0.0,"currency_code":"GBP","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0784\/4072\/6801\/files\/0898596092.jpg?v=1751363966"},{"product_id":"statistical-language-learning-book-eugene-charniak-9780262531412","title":"Statistical Language Learning","description":"\u003cp\u003eEugene Charniak breaks new ground in artificial intelligence research by presenting statistical language processing from an artificial intelligence point of view in a text for researchers and scientists with a traditional computer science background. New, exacting empirical methods are needed to break the deadlock in such areas of artificial intelligence as robotics, knowledge representation, machine learning, machine translation, and natural language processing (NLP). It is time, Charniak observes, to switch paradigms. This text introduces statistical language processing techniques; word tagging, parsing with probabilistic context free grammars, grammar induction, syntactic disambiguation, semantic wordclasses, word-sense disambiguation; along with the underlying mathematics and chapter exercises. Charniak points out that as a method of attacking NLP problems, the statistical approach has several advantages. It is grounded in real text and therefore promises to produce usable results, and it offers an obvious way to approach learning: one simply gathers statistics.\u003c\/p\u003e","brand":"WoB","offers":[{"title":"US \/ GOOD \/ SBYB","offer_id":50346397335825,"sku":"CIN0262531410G","price":0.0,"currency_code":"GBP","in_stock":true},{"title":"GB \/ VERY_GOOD \/ INTERNAL","offer_id":50657474707729,"sku":"GOR006483121","price":0.0,"currency_code":"GBP","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0784\/4072\/6801\/files\/0262531410.jpg?v=1751290788"},{"product_id":"ai-i-book-eugene-charniak-9780262548731","title":"AI \u0026 I","description":"\u003cb\u003eOne of AI's earliest and most respected pioneers offers a concise, illuminating history of artificial intelligence-and champions a deep learning approach for future developments.\u003c\/b\u003e\u003cbr\u003e \u003cbr\u003e \u003ci\u003eAI \u0026amp; I\u003c\/i\u003e is an intellectual history of the field of artificial intelligence from the perspective of one of its first practitioners, Eugene Charniak. Charniak entered the field in 1967, roughly 12 years after AI's founding, and was involved in many of AI's formative milestones. In this book, he traces the trajectory of breakthroughs and disappointments of the discipline up to the current day, clearly and engagingly demystifying this oft revered and misunderstood technology. His argument is controversial but well supported- that classical artificial intelligence has been almost uniformly unsuccessful and that the modern deep learning approach should be viewed as the foundation for all the exciting developments that are to come.\u003cbr\u003e \u003cbr\u003e Written for the scientifically educated layperson, this book chronicles the history of the field of artificial intelligence, starting with its origin in 1956, as a topic for a small academic workshop held at Dartmouth University. From there, the author covers reasoning and knowledge representation, reasoning under uncertainty, chess, computer vision, speech recognition, language acquisition, deep learning, and learning writ large. Ultimately, Charniak takes issue with the controversy of AI-the fear that its invention means the end of jobs, creativity, and potentially even humans as a species-and explains why such concerns are unfounded. 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