dnnagy Goto Github PK

asr_tf_pytorch

notebook

awesome-cheatsheets

👩‍💻👨‍💻 Awesome cheatsheets for popular programming languages, frameworks and development tools. They include everything you should know in one single file.

biophys-seminar

Hopfield nets

bqit21-posters

clip-interrogator

Image to prompt with BLIP and CLIP

coding_cup_ai

DQN version of coding tomorrow cup

deeplearningcourse

The official repository of Deep learning and machine learning in science (deeplea17em) course @ ELTE.

dslab2019-project

My Project for dslab2019

fiznum2

Fizika numerikus módszerei II. beadandók

infocom-networks

Infocom networks assignments

jupyter-notebook-base

Dockerfile for nagyd96/jupyter-notebook-base

kvantum

Kvantummechanika gyorstalpaló és képletgyűjtemény

kwantproject

Kwant project for the course 'Scientific Modelling Computer Lab 2018-19/2'.

libstft

Small stft library in C++ and Python

libtorch-ios

iOS tests for libtorch

llvm-bitcode-test

Test generating llvm bitcode with cmake

lte-simulation-in-ns3

Simulation of a full-fledged LTE network in using the network simulator, NS3

mezo2019

microserver-ios

A very basic http server based on the https://github.com/httpswift/swifter project.

msc-thesis

msc-thesis-final

myweight

I'm logging my weight (almost) daily.

nodecheckbox

Simple solution for sending multiple checkbox values with ajax to a nodejs server.

ns3-ai

Enable the interaction between ns-3 and popular frameworks using Python, which mean you can train and test your AI algorithms in ns-3 without changing any frameworks you are using now!

ns3-gym

ns3-gym - The Playground for Reinforcement Learning in Networking Research

ns3-mmwave

ns-3 module for simulating mmWave-based cellular systems. See https://ieeexplore.ieee.org/document/8344116/ (open access) as a reference.

pystft

Simple STFT library in Python using fftpack and C++/Python bindings

qintro

Introduction to quantum algorithms with qiskit

qiskit-notebook

qiskit notebooks based on dnnagy/jupyter-notebook-base

qml-mooc

Lecture notebooks and coding assignments for the quantum machine learning MOOC created by Peter Wittek on EdX in the Spring 2019