Search Results for "machine learning python"

System Design Primer is a curated, open source collection of resources that helps engineers learn how to design large-scale systems. The project is structured as a comprehensive guide covering core system design concepts, trade-offs, and patterns necessary for building scalable, reliable, and maintainable systems. It offers both theoretical foundations—such as scalability principles, the CAP theorem, and consistency models—and practical exercises, including real-world system design interview...

...It is useful for people who want to display habits, reading, coding, health, language learning, or other quantified-life records in a GitHub-inspired format. It can be run locally from the command line and can also be automated through GitHub Actions. Its modular approach makes it possible for contributors to add new data sources over time.

The tensorflow-haskell package provides Haskell-language bindings for TensorFlow, giving Haskell developers the ability to build and run computation graphs, machine learning models, and leverage TensorFlow's ecosystem—though it is not an official Google release. As an expedient we use docker for building. Once you have docker working, the following commands will compile and run the tests. Run the install_macos_dependencies.sh script in the tools/ directory. The script installs dependencies via Homebrew and then downloads and installs the TensorFlow library on your machine under /usr/local. ...

A graphical tool for designing finite state machines and exporting them to Hardware Description Languages, such as VHDL, AHDL, Verilog, or Ragel/SMC files for C, C++, Objective-C, Java, Python, PHP, Perl, Lua code generation.