David Leonardi's repositories
Armenian_Online_Job_Postings_Text_Mining
Text mining of a job postings dataset to derive insights
AZ-900T0x-MicrosoftAzureFundamentals
Microsoft Azure Fundamentals - AZ-900T00 and AZ-900T01
braindecode
A deep learning toolbox to decode raw time-domain EEG. Modified version of this repo: https://robintibor.github.io/braindecode/
dataeng_test
Data Engineering Test
ffhq-dataset
Flickr-Faces-HQ Dataset (FFHQ)
flink-playgrounds
Apache Flink Playgrounds
LeagueofLegends_Matches_Analysis
Data analysis on League of Legends dataset.
markdown2pdf
[Deprecated] A command line tool to convert markdown file to pdf.
mml-book.github.io
Companion webpage to the book "Mathematics For Machine Learning"
nakamura41.github.io
My Resume Page
practical-pytorch
PyTorch tutorials demonstrating modern techniques with readable code
progressive_growing_of_gans
Progressive Growing of GANs for Improved Quality, Stability, and Variation
pytorch-summary
Model summary in PyTorch similar to `model.summary()` in Keras
Seq2Seq_Eng2Indo
A Pytorch-based Seq2Seq model translating English to Bahasa Indonesia
simple-salesforce
A very simple Salesforce.com REST API client for Python
stockpredictionai
In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.
unify-emotion-datasets
A Survey and Experiments on Annotated Corpora for Emotion Classification in Text