Nikolaos Dionelis's repositories
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
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.
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.
Deep-Learning-Boot-Camp
A community run, 5-day PyTorch Deep Learning Bootcamp
dl-imperial-maths
Code and assignment repository for the Imperial College Mathematics department Deep Learning course
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.
mml-book.github.io
Companion webpage to the book "Mathematics For Machine Learning"
phd-bibliography
References on Optimal Control, Reinforcement Learning and Motion Planning
PythonMachineLearning
Practice and tutorial-style notebooks covering wide variety of machine learning techniques
TensorFlow-Course
Simple and ready-to-use tutorials for TensorFlow
DeepLearningProject
An in-depth machine learning tutorial introducing readers to a whole machine learning pipeline from scratch.
keras-applications
Reference implementations of popular deep learning models.
maskrcnn-benchmark
Fast, modular reference implementation of Semantic Segmentation and Object Detection algorithms in PyTorch.
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.
text_classification
all kinds of text classificaiton models and more with deep learning
gradnorm_ood
On the Importance of Gradients for Detecting Distributional Shifts in the Wild