nd1511
Nikolaos is a postgraduate researcher in the Speech and Audio Processing Group in the Department of Electrical Engineering at Imperial College London (ICL).
Imperial College London, London, U.K.London, U.K.
Pinned Repositories
amazon-sagemaker-examples
Example notebooks that show how to apply machine learning and deep learning in Amazon SageMaker
awesome-python
A curated list of awesome Python frameworks, libraries, software and resources
coding-interview-university
A complete computer science study plan to become a software engineer.
OMASGAN_
OoD Minimum Anomaly Score GAN - Code for the Paper 'OMASGAN: Out-of-Distribution Minimum Anomaly Score GAN for Sample Generation on the Boundary'
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"
PythonProgramming
Python Programming
PyTorch-Tutorial-1
Build your neural network easy and fast
RepoRepository
MyRepoRepository
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.
nd1511's Repositories
nd1511/PythonProgramming
Python Programming
nd1511/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 ;)
nd1511/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"
nd1511/OMASGAN_
OoD Minimum Anomaly Score GAN - Code for the Paper 'OMASGAN: Out-of-Distribution Minimum Anomaly Score GAN for Sample Generation on the Boundary'
nd1511/PyTorch-Tutorial-1
Build your neural network easy and fast
nd1511/RepoRepository
MyRepoRepository
nd1511/amazon-sagemaker-examples
Example notebooks that show how to apply machine learning and deep learning in Amazon SageMaker
nd1511/coding-interview-university
A complete computer science study plan to become a software engineer.
nd1511/lucid
A collection of infrastructure and tools for research in neural network interpretability.
nd1511/awesome-deep-learning
A curated list of awesome Deep Learning tutorials, projects and communities.
nd1511/awesome-machine-learning
A curated list of awesome Machine Learning frameworks, libraries and software.
nd1511/Deep-Learning-Boot-Camp
A community run, 5-day PyTorch Deep Learning Bootcamp
nd1511/dl-imperial-maths
Code and assignment repository for the Imperial College Mathematics department Deep Learning course
nd1511/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.
nd1511/hub
A library for transfer learning by reusing parts of TensorFlow models.
nd1511/mml-book.github.io
Companion webpage to the book "Mathematics For Machine Learning"
nd1511/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
nd1511/phd-bibliography
References on Optimal Control, Reinforcement Learning and Motion Planning
nd1511/PythonMachineLearning
Practice and tutorial-style notebooks covering wide variety of machine learning techniques
nd1511/TensorFlow-Course
Simple and ready-to-use tutorials for TensorFlow
nd1511/DeepLearningProject
An in-depth machine learning tutorial introducing readers to a whole machine learning pipeline from scratch.
nd1511/keras-applications
Reference implementations of popular deep learning models.
nd1511/maskrcnn-benchmark
Fast, modular reference implementation of Semantic Segmentation and Object Detection algorithms in PyTorch.
nd1511/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.
nd1511/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.
nd1511/Python
All Algorithms implemented in Python
nd1511/text_classification
all kinds of text classificaiton models and more with deep learning
nd1511/vos
source code for ICLR'22 paper "VOS: Learning What You Don’t Know by Virtual Outlier Synthesis"
nd1511/gradnorm_ood
On the Importance of Gradients for Detecting Distributional Shifts in the Wild
nd1511/resume
My resume