Deep Learning: DL1943 Cheatsheet: DL/AI/ML Research, Engineering, Optimization & System DesignКНИГИ » ПРОГРАММИНГ
Название: Deep Learning: DL1943 Cheatsheet: DL/AI/ML Research, Engineering, Optimization & System Design Автор: Calder Reed, Chen Hui Fang Издательство: Independently published Год: 2025 Страниц: 150 Язык: английский Формат: pdf, epub Размер: 12.7 MB
This book "Deep Learning: DL1943 Cheatsheet: DL/AI/ML Research, Engineering, Optimization & System Design" is the only book you need to master Deep Learning (DL) concepts. The focus is on practical research and engineering ideas.
This is a cheatsheet just like distilled datasets. You do not need to read 1000s of pages. Just 150 pages is enough to revise the cutting-edge Deep Learning engineering and research ideas.
This book include:
Chapters covering all core concepts in DL research, engineering and optimization including: Basic concepts like Perceptron, Gradient Descent All basic terms like epoch, topK and basic ops like MaxPool Concepts to run algorithms in parallel in GPU and CPU Core techniques like INT8 Quantization Deep Learning System Design (with examples) Numerical Analysis concepts like INT32 IEEE754, emulating FP64 using FP32. Model architectures from MLP to CNN to LLM. Optimization techniques across: Assembly instructions like AVX512 VNNI Algorithmic optimizations for DL operations like MatMul Graph level operations and much more. Each chapter is a CHEATSHEET. It includes to-the-point explanation and relevant code snippets. Each concept can be covered quickly in at most 4 minutes. Over 350 DL/AI concepts have been covered.
With this, you will be able to crack any Deep Learning Coding Interview easily.
After reading this book, you will:
Master Deep Learning/ Artificial Intelligence. Clear interviews for full-time positions at high-tech companies. Good enough for: Software Engineer 2/3, Machine Learning or Senior Software Engineer, AI/ML GenAI or ML Analyst at Google (L3/L4/L5) Software Engineer, Machine Learning (E4/E5/E6) at Meta Senior Deep Learning Systems Software Engineer - AI or AI Developer Technology Engineer at NVIDIA Kernel Software Engineer - AI/ML GPU or Senior Machine Learning Software Engineer at AMD Lead Engineer, Senior-C/C++, machine learning at Qualcomm Machine Learning Engineer at Microsoft (Level 60 to 66) And much more.
This book is for:
Students and developers preparing for Coding Interviews specifically for Machine Learning/Deep Learning/GenAI positions. Experienced developers who wanted to revise their Deep Learning skills. Students who need a coding sheet to revise DL/AI/ML topics quickly.
Get started with this book and change the equation of your career.
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Deep Learning: DL1943 Cheatsheet: DL/AI/ML Research, Engineering, Optimization & System Design 
