ai's Projects
Exercises and supplementary material for the deep learning course 02456 using PyTorch.
Config files for my GitHub profile.
Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes
PyTorch Tutorial - Workshop at the AMLD 2020
Examples of how to create colorful, annotated equations in Latex using Tikz.
A data augmentations library for audio, image, text, and video.
In this repository, you can find my contributions to the Real World Data Science website (https://realworlddatascience.net/), a project from the Royal Statistical Society.
List of Computer Science courses with video lectures.
Productivity Tools for Plotly + Pandas
Deep Learning Specialization by Andrew Ng on Coursera.
Deep learning codes and projects using Python
Notebooks from Coursera
A playbook for systematically maximizing the performance of deep learning models.
This repository contains files to employ t-SNE to visualize various local environments of atoms in L10-FeNi.
Over 200 figures and diagrams of the most popular deep learning architectures and layers FREE TO USE in your blog posts, slides, presentations, or papers.
Notebooks for learning deep learning
Material for AMLD 2020 workshop "Bayesian Inference: embracing uncertainty"
Set of notebooks going deeper on understanding some classical approaches on exploratory data analysis
An easy to use blogging platform, with enhanced support for Jupyter Notebooks.
Generates a NxNxN FCC supercell and assigns random first nearest neighbor couplings
Feature engineering techniques to improve the performance of ML models in Fraud detection
Create UIs for your machine learning model in Python in 3 minutes
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
Introduction to Jupyter Notebook
Jupyter Notebooks as Markdown Documents, Julia, Python or R scripts
Kinetic-Monte-Carlo code implemented in Python to investigate the hydrogen diffusion in Fe-Mn-Al alloys.
MS analysis pipeline using matchms