Nikolaos Dionelis (nd1511)

nd1511

Geek Repo

Company:Imperial College London, London, U.K.

Location:London, U.K.

Home Page:https://www.commsp.ee.ic.ac.uk/~sap/people-nikolaos-dionelis/

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Nikolaos Dionelis's repositories

PythonProgramming

Python Programming

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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 ;)

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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"

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PyTorch-Tutorial-1

Build your neural network easy and fast

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OMASGAN_

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

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RepoRepository

MyRepoRepository

amazon-sagemaker-examples

Example notebooks that show how to apply machine learning and deep learning in Amazon SageMaker

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coding-interview-university

A complete computer science study plan to become a software engineer.

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lucid

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

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awesome-deep-learning

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

awesome-machine-learning

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

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Deep-Learning-Boot-Camp

A community run, 5-day PyTorch Deep Learning Bootcamp

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dl-imperial-maths

Code and assignment repository for the Imperial College Mathematics department Deep Learning course

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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.

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hub

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

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mml-book.github.io

Companion webpage to the book "Mathematics For Machine Learning"

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

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phd-bibliography

References on Optimal Control, Reinforcement Learning and Motion Planning

PythonMachineLearning

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

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TensorFlow-Course

Simple and ready-to-use tutorials for TensorFlow

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DeepLearningProject

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

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keras-applications

Reference implementations of popular deep learning models.

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maskrcnn-benchmark

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

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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.

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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.

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Python

All Algorithms implemented in Python

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text_classification

all kinds of text classificaiton models and more with deep learning

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gradnorm_ood

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

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resume

My resume

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vos

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

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