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MarkoShiva/README.md

Hi and welcome to my github

  • 🔭 I’m currently working on consulting roles and backend web development roles. :D

  • 🔭 I sometime spend time implementing or reimplementing things in golang and rust. Like WebRTC suite.

  • 🔭 I am available for:

    • Web Development jobs, mainly API implementations as well FullStack roles. However my prefered backend is Python.
    • optimisation of existing applications and infrastructure development with python, C++ golang rust.
    • Machine Learning postions and startup companies that are trying to solve interesting tasks via Machine Learning.
  • Favorite languages:

    • Python
    • C++
    • Dart/Flutter
    • Typescript
    • rust
    • Java
  • 🌱 I’m currently learning:

    • Machine Learning areas like the implementation of TensorFlow.
    • Dart - Flutter - Typescript.
    • anyhthing web development related that is needed for success of my projects.
  • 👯 I'm trying to find more time for working oncolaboration projects in FLOSS mainly google backed projects like TensorFlow, Dart Flutter.

  • 💬 Ask me about Linux C++ development. Kernel Networking Stack. Python and API development or Mathematical Theories of Computational Universe or SuperString theory explanations something Machine Learning related, and we might have a nice conversation. Its tensors all the way down baby. :)

  • 📫 How to reach me: there are enough links here. :)

  • 😄 Pronouns: He/Him



Technologies I use

Pinned Loading

  1. opensnitch opensnitch Public

    Forked from evilsocket/opensnitch

    OpenSnitch is a GNU/Linux port of the Little Snitch application firewall

    Python 1

  2. linux linux Public

    Forked from torvalds/linux

    Linux kernel source tree

    C

  3. Quaternion Quaternion Public

    Forked from quotient-im/Quaternion

    A Qt5-based IM client for Matrix

    C++

  4. kscreenlocker kscreenlocker Public

    Forked from KDE/kscreenlocker

    Library and components for secure lock screen architecture.

    C++

  5. ARS ARS Public

    Implementation of the Augmented Random Search following the paper of research team from Berkeley (https://arxiv.org/abs/1803.07055) with numpy.

    Python 1