Publisher's Synopsis
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. Book: Deep Learning: DL1943 Cheatsheet: DL/AI/ML Research, Engineering, Optimization & System Design
Authors (2): Calder Reed, Chen Hui Fang
Published: February 2025 (Edition 1)
