《HTTP/2 Protocol Analysis》This series article detailed analysis the RFC 7540, which is the Hypertext Transfer Protocol Version 2 (HTTP/2).
• [RFC 7540] Hypertext Transfer Protocol Version 2 (HTTP/2) • Unveiling the veil of HTTP/2: How does HTTP/2 establish a connection? • Multiplexing of HTTP frames and streams in HTTP/2 • Frame definition in HTTP/2 • HTTP semantics in HTTP/2 • Considerations in HTTP/2 • Frequently asked questions in HTTP/2 • [RFC 7541] HPACK: Header Compression for HTTP/2 • Detailed HTTP/2 header compression algorithm-HPACK • HTTP/2 HPACK practical application examples • [RFC 7301] TLS Application-Layer Protocol Negotiation Extension
《TLS 1.3 Protocol Analysis》This series article detailed analysis the RFC 8846, which is the Transport Layer Security (TLS) Protocol Version 1.3.
• How to deploy TLS 1.3 ? • [RFC 6520] TLS & DTLS Heartbeat Extension • [RFC 8446] The Transport Layer Security (TLS) Protocol Version 1.3 • TLS 1.3 Introduction • TLS 1.3 Handshake Protocol • TLS 1.3 Record Protocol • TLS 1.3 Alert Protocol • TLS 1.3 Cryptographic Computations • TLS 1.3 0-RTT and Anti-Replay • TLS 1.3 Compliance Requirements • TLS 1.3 Implementation Notes • TLS 1.3 Backward Compatibility • TLS 1.3 Overview of Security Properties
《Study Notes of Machine Learning》This study notes is the machine learning course in the coursera, which it’s instructor is Andrew Ng in the Stanford University.
• Week1 —— What is Machine Learning • Week1 —— Linear Regression with One Variable (Gradient Descent) • Week2 —— Multivariate Linear Regression • Week2 —— Computing Parameters Analytically • Week2 —— Octave Matlab Tutorial • Week3 —— Logistic Regression • Week3 —— Regularization • Week4 —— Neural Networks Representation • Week5 —— Neural Networks Learning • Week5 —— Backpropagation in Practice • Week6 —— Advice for Applying Machine Learning • Week6 —— Machine Learning System Design • Week7 —— Support Vector Machines • Week8 —— Unsupervised Learning • Week8 —— Dimensionality Reduction • Week9 —— Anomaly Detection • Week9 —— Recommender Systems • Week10 —— Large Scale Machine Learning • Week11 —— Application Example: Photo OCR