Nikolaos Dionelis

PythonProgramming. Python Programming

Probabilistic-Programming-and-Bayesian-Methods-for-Hackers. aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)

Proof-Of-Concept. Proof Of Concept: Obtaining Graphs Like Fig. 4 in the Paper "Phase-Aware Single-Channel Speech Enhancement with Modulation-Domain Kalman Filtering"

PyTorch-Tutorial-1. Build your neural network easy and fast

OMASGAN_. OoD Minimum Anomaly Score GAN - Code for the Paper 'OMASGAN: Out-of-Distribution Minimum Anomaly Score GAN for Sample Generation on the Boundary'

awesome-python. A curated list of awesome Python frameworks, libraries, software and resources

Theano. Theano is a Python library that allows you to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently. It can use GPUs and perform efficient symbolic differentiation.

RepoRepository. MyRepoRepository

amazon-sagemaker-examples. Example notebooks that show how to apply machine learning and deep learning in Amazon SageMaker

coding-interview-university. A complete computer science study plan to become a software engineer.

DeepLearningProject. An in-depth machine learning tutorial introducing readers to a whole machine learning pipeline from scratch.

lucid. A collection of infrastructure and tools for research in neural network interpretability.

PythonMachineLearning. Practice and tutorial-style notebooks covering wide variety of machine learning techniques

pandas. Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more

phd-bibliography. References on Optimal Control, Reinforcement Learning and Motion Planning

dl-imperial-maths. Code and assignment repository for the Imperial College Mathematics department Deep Learning course

awesome-machine-learning. A curated list of awesome Machine Learning frameworks, libraries and software.

mml-book.github.io. Companion webpage to the book "Mathematics For Machine Learning"

hub. A library for transfer learning by reusing parts of TensorFlow models.

awesome-deep-learning. A curated list of awesome Deep Learning tutorials, projects and communities.

handson-ml. A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.

TensorFlow-Course. Simple and ready-to-use tutorials for TensorFlow

Deep-Learning-Boot-Camp. A community run, 5-day PyTorch Deep Learning Bootcamp

maskrcnn-benchmark. Fast, modular reference implementation of Semantic Segmentation and Object Detection algorithms in PyTorch.

edward. A probabilistic programming language in TensorFlow. Deep generative models, variational inference.

text_classification. all kinds of text classificaiton models and more with deep learning

adanet. Fast and flexible AutoML with learning guarantees.

MMdnn. MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, PyTorch Onnx and CoreML.

ML-From-Scratch. Machine Learning From Scratch. Bare bones Python implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from data mining to deep learning.

keras-applications. Reference implementations of popular deep learning models.

Python. All Algorithms implemented in Python

SincNet. SincNet is a neural architecture for efficiently processing raw audio samples.

vos. source code for ICLR'22 paper "VOS: Learning What You Don’t Know by Virtual Outlier Synthesis"

ignite. High-level library to help with training neural networks in PyTorch

resume. My resume

tensorpack. A Neural Net Training Interface on TensorFlow

pygcn. Graph Convolutional Networks in PyTorch

tutorials-1. Caffe2 Tutorials

gradnorm_ood. On the Importance of Gradients for Detecting Distributional Shifts in the Wild

pyannote-audio. Neural building blocks for speaker diarization: speech activity detection, speaker change detection, speaker embedding

PConv-Keras. Keras implementation of "Image Inpainting for Irregular Holes Using Partial Convolutions"

bayarea-dl-summerschool. Torch notebooks and slides for the Bay Area Deep Learning Summer School

PySurfer. Cortical neuroimaging visualization in Python

blocks. A Theano framework for building and training neural networks

pytorch2keras. Pytorch to Keras model convertor

trfl. TensorFlow Reinforcement Learning

fastai. The fastai deep learning library, plus lessons and and tutorials

rethinking-network-pruning. Rethinking the Value of Network Pruning (Pytorch)

incubator-mxnet. Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more

librosa. Python library for audio and music analysis

DeepSpeech. A TensorFlow implementation of Baidu's DeepSpeech architecture

AaltoASR. Aalto Automatic Speech Recognition tools

AIND-VUI-Capstone. AIND Term 2 -- VUI Capstone Project

modeling-nonlinear. Audio examples for the paper 'Modeling of nonlinear audio effects with end-to-end deep neural networks'

keras-rl. Deep Reinforcement Learning for Keras.

tf-pose-estimation. Deep Pose Estimation implemented using Tensorflow with Custom Architectures for fast inference.

Seq2Seq-PyTorch. Sequence to Sequence Models with PyTorch

source-separation-anchors. Python package for generating anchor stimuli suitable for the subjective evaluation of source separation algorithms

deepface. Deep Learning Models for Face Detection/Recognition/Alignments, implemented in Tensorflow

untwist. Python