{"product_id":"deep-learning-chen-hui-fang-9798310930803","title":"Deep Learning: DL1943 Cheatsheet: DL\/AI\/ML Research, Engineering, Optimization \u0026 System Design","description":"This book \"\u003cb\u003eDeep Learning: DL1943 Cheatsheet: DL\/AI\/ML Research, Engineering, Optimization \u0026amp; System Design\u003c\/b\u003e\" is the only book you need to master Deep Learning (DL) concepts. The focus is on practical research and engineering ideas. \u003cp\u003e\u003c\/p\u003e\u003ci\u003eThis is a \u003c\/i\u003e\u003cb\u003echeatsheet\u003c\/b\u003e\u003ci\u003e just like \u003c\/i\u003e\u003cb\u003edistilled datasets\u003c\/b\u003e\u003ci\u003e.\u003c\/i\u003e\u003cbr\u003eYou do not need to read 1000s of pages. Just 150 pages is enough to revise the cutting-edge Deep Learning engineering and research ideas. \u003cp\u003e\u003c\/p\u003eThis book include: \u003cul\u003e\n\u003cli\u003eChapters covering all core concepts in DL research, engineering and optimization including: \u003cul\u003e\n\u003cli\u003eBasic concepts like Perceptron, Gradient Descent\u003c\/li\u003e\n\u003cli\u003eAll basic terms like epoch, topK and basic ops like MaxPool\u003c\/li\u003e\n\u003cli\u003eConcepts to \u003cb\u003erun algorithms in parallel in GPU and CPU\u003c\/b\u003e\n\u003c\/li\u003e\n\u003cli\u003eCore techniques like \u003cb\u003eINT8 Quantization\u003c\/b\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cb\u003eDeep Learning System Design\u003c\/b\u003e (with examples)\u003c\/li\u003e\n\u003cli\u003e\n\u003cb\u003eNumerical Analysis\u003c\/b\u003e concepts like INT32 IEEE754, emulating FP64 using FP32.\u003c\/li\u003e\n\u003cli\u003eModel architectures from MLP to CNN to LLM.\u003c\/li\u003e\n\u003cli\u003e\n\u003cb\u003eOptimization techniques\u003c\/b\u003e across: \u003cul\u003e\n\u003cli\u003eAssembly instructions like \u003cb\u003eAVX512 VNNI\u003c\/b\u003e\n\u003c\/li\u003e\n\u003cli\u003eAlgorithmic optimizations for DL operations like \u003cb\u003eMatMul\u003c\/b\u003e\n\u003c\/li\u003e\n\u003cli\u003eGraph level operations\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/li\u003e\n\u003cli\u003eand much more.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/li\u003e\n\u003cli\u003eEach chapter is a \u003cb\u003eCHEATSHEET\u003c\/b\u003e. It includes to-the-point explanation and relevant code snippets.\u003c\/li\u003e\n\u003cli\u003eEach concept can be covered quickly in at most 4 minutes.\u003c\/li\u003e\n\u003cli\u003eOver 350 DL\/AI concepts have been covered.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cbr\u003eWith this, you will be able to crack any Deep Learning Coding Interview easily. \u003cp\u003e\u003c\/p\u003eAfter reading this book, you will: \u003cul\u003e\n\u003cli\u003eMaster Deep Learning\/ Artificial Intelligence.\u003c\/li\u003e\n\u003cli\u003eClear interviews for full-time positions at high-tech companies. Good enough for: \u003cul\u003e\n\u003cli\u003eSoftware Engineer 2\/3, Machine Learning or Senior Software Engineer, AI\/ML GenAI or ML Analyst at \u003cb\u003eGoogle\u003c\/b\u003e (L3\/L4\/L5)\u003c\/li\u003e\n\u003cli\u003eSoftware Engineer, Machine Learning (E4\/E5\/E6) at \u003cb\u003eMeta\u003c\/b\u003e\n\u003c\/li\u003e\n\u003cli\u003eSenior Deep Learning Systems Software Engineer - AI or AI Developer Technology Engineer at \u003cb\u003eNVIDIA\u003c\/b\u003e\n\u003c\/li\u003e\n\u003cli\u003eKernel Software Engineer - AI\/ML GPU or Senior Machine Learning Software Engineer at \u003cb\u003eAMD\u003c\/b\u003e\n\u003c\/li\u003e\n\u003cli\u003eLead Engineer, Senior-C\/C++, machine learning at \u003cb\u003eQualcomm\u003c\/b\u003e\n\u003c\/li\u003e\n\u003cli\u003eMachine Learning Engineer at \u003cb\u003eMicrosoft\u003c\/b\u003e (Level 60 to 66)\u003c\/li\u003e\n\u003cli\u003eAnd much more.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/li\u003e\n\u003c\/ul\u003e\u003cbr\u003eThis book is for: \u003cul\u003e\n\u003cli\u003eStudents and developers preparing for Coding Interviews specifically for Machine Learning\/Deep Learning\/GenAI positions.\u003c\/li\u003e\n\u003cli\u003eExperienced developers who wanted to revise their Deep Learning skills.\u003c\/li\u003e\n\u003cli\u003eStudents who need a coding sheet to revise DL\/AI\/ML topics quickly.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cbr\u003eGet started with this book and change the equation of your career. \u003cp\u003e\u003c\/p\u003eBook: \u003cb\u003eDeep Learning: DL1943 Cheatsheet: DL\/AI\/ML Research, Engineering, Optimization \u0026amp; System Design\u003c\/b\u003e\u003cbr\u003eAuthors (2): Calder Reed, Chen Hui Fang\u003cbr\u003ePublished: February 2025 (Edition 1)\u003cbr\u003e\u003cbr\u003e\u003cb\u003eAuthor:\u003c\/b\u003e Chen Hui Fang, Calder Reed\u003cbr\u003e\u003cb\u003eISBN-13:\u003c\/b\u003e 9798310930803\u003cbr\u003e\u003cb\u003ePublisher:\u003c\/b\u003e Independently Published\u003cbr\u003e\u003cb\u003eLanguage:\u003c\/b\u003e English\u003cbr\u003e\u003cb\u003ePublished:\u003c\/b\u003e 02\/23\/2025\u003cbr\u003e\u003cb\u003ePages:\u003c\/b\u003e 150\u003cbr\u003e\u003cb\u003eFormat:\u003c\/b\u003e Paperback\u003cbr\u003e\u003cb\u003eWeight:\u003c\/b\u003e 0.60lbs\u003cbr\u003e\u003cb\u003eSize:\u003c\/b\u003e 10.00h x 7.00w x 0.32d","brand":"Chen Hui Fang","offers":[{"title":"Paperback","offer_id":46907235139839,"sku":"9798310930803","price":29.97,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0662\/2982\/9887\/files\/img_21d7b288-54d7-42b8-8e77-427668dbd26e.jpg?v=1748772724","url":"https:\/\/www.whiterainbookhouse.com\/products\/deep-learning-chen-hui-fang-9798310930803","provider":"WR Book House","version":"1.0","type":"link"}