Vision-Language Adapters: Efficient Fine-tuning
Master LoRA, bottleneck adapters, and prefix tuning for parameter-efficient fine-tuning of vision-language models like LLaVA with minimal compute and memory.
Clear explanations of core machine learning concepts, from foundational ideas to advanced techniques. Understand attention mechanisms, transformers, skip connections, and more.
Master LoRA, bottleneck adapters, and prefix tuning for parameter-efficient fine-tuning of vision-language models like LLaVA with minimal compute and memory.
Learn client-server communication patterns including short polling, long polling, and WebSockets. Compare HTTP protocols for real-time web applications.
Explore how C++ code is parsed into an Abstract Syntax Tree (AST). Learn lexical analysis, tokenization, and syntax parsing for systems programming.
Understand the complete C++ compilation pipeline from source code to object files. Learn preprocessing, parsing, code generation, and optimization stages.
Deep dive into dynamic linking — GOT/PLT lazy resolution, shared library creation, SONAME versioning, RPATH/RUNPATH, dlopen plugin systems, LD_PRELOAD, and debugging with LD_DEBUG.
How C++ object files are linked into executables. Learn symbol resolution, static vs dynamic linking, and linker optimization.