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Full Description
Silicon Valley Python Interview Guide: Data Structures, Algorithms, and System Design is an essential resource for aspiring software engineers preparing for technical interviews at top-tier companies. This book provides a comprehensive roadmap, covering foundational concepts, practical coding techniques, and advanced problem-solving strategies to help candidates excel in interviews. With a focus on Python, the book equips readers with the skills to tackle challenging coding problems, design scalable systems, and communicate solutions effectively. In the first half, the book delves into core data structures (lists, stacks, queues, graphs, and trees) and algorithms (binary search, dynamic programming, DFS, BFS, and backtracking),offering practical examples and Python implementations. The latter half transitions to system design, including big data architectures, distributed systems, and machine learning workflows. Case studies on real-world applications like Tiny URL, autocomplete systems, and Chat GPT-like models provide hands-on insights. Whether you are an early-career engineer or an experienced professional, this guide is designed to enhance your preparation with real-world examples, tested code, and proven strategies. It is more than a technical handbook—it is your roadmap to building confidence and securing a role in the competitive tech industry.
Contents
Chapter 1 Technical Interview process.- Part I: Data Structures.- Chapter 2 List.- Chapter 3 Stack.- Chapter 4 Queue.- Chapter 5 Priority queues.- Chapter 6 Dictionary.- Chapter 7 Sets.- Chapter 8 Linked lists.- Chapter 9 Binary tree.- Chapter 10 Some other tree structures.- Chapter 11 Graph.- Part II Algorithmic Part.- Chapter 12 Binary Search.- Chapter 13 Two-pointer method.- Chapter 14 Dynamic programming.- Chapter 15 Depth First Search.- Chapter 16 Backtracking.- Chapter 17 Breadth First Search.- Chapter 18 Union Find.- Chapter 19 Interview questions.- Part III: System Design.- Chapter 20 System Design Theory.- Chapter 21 System Design Practice for big data 6.- Chapter 22 Multi-threaded programming.- Chapter 23 Machine Learning System Design.- Chapter 24 Large Language Model system design.
