Automata and Compilers 08 - Bottom-Up Parsing
Shift-reduce parsing, LR parser mechanics, and how parser generators work under the hood
Thoughts on code, technology, and everything in between
Building reliable ML systems from data pipelines to production monitoring
From finite automata and formal languages to building a compiler from scratch
Understanding the Linux kernel from processes and memory to containers
Understanding the principles behind Internal Developer Platforms, golden paths, and developer self-service
Comprehensive Python programming course from basics to advanced topics
Shift-reduce parsing, LR parser mechanics, and how parser generators work under the hood
How a system call transitions from user space to kernel space, and how kernel modules work
How developer portals like Backstage bring order to the chaos of scattered docs, tools, and tribal knowledge
How to serve trained models in production and deploy them safely
How VFS, inodes, and ext4 work in the world where everything is a file
The principles behind recursive descent parsers, LL(1) grammars, and the strengths and limitations of top-down parsing
Why model versioning differs from code versioning, and the role of a model registry
Why IaC is the backbone of any platform, and how tools like Terraform, Pulumi, and Crossplane compare when building self-service infrastructure
How a lexer breaks source code into tokens and where automata theory meets real implementation