This course covers the design and implementation of distributed systems. Students will gain an understanding of the principles and techniques behind the design of modern, reliable, and high-performance distributed systems. Topics include server design, network programming, naming, concurrency and locking, consistency models and techniques, security, and fault tolerance. Modern techniques and systems employed at some of the largest Internet sites (e.g., Google, Facebook, Amazon) will also be covered. Through programming assignments, students will gain practical experience designing, implementing, and debugging real distributed systems.
What will future historians will see as the major Russian contribution to early 21st-century Internet culture? It might not be troll farms and other strategies for poisoning public conversation — but rather, the democratization of access to scientific and scholarly knowledge.
- Understanding the GitHub Flow
- Hello World
- Getting Started with GitHub Pages
- Git Handbook
- Forking Projects
- Be Social
- Making Your Code Citable
- Mastering Issues
- Mastering Markdown
- Documenting your projects on GitHub
This blog is a part of "A Guide To TensorFlow", where we will explore the TensorFlow API and use it to build multiple machine learning models for real- life examples. In this blog we shall uncover TensorFlow *Graph*, understand the concept of *Tensors* and also explore TensorFlow data types.