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awesome-datascience

:memo: An awesome Data Science repository to learn and apply for real world problems.

awesome-graph

A curated list of resources for graph databases and graph computing tools

awesome-italian-public-datasets

A selection of interesting Open dataset from the Italian Public Administration and Civic Data use cases

awesome-public-datasets

A topic-centric list of HQ open datasets.

awesome-python

A curated list of awesome Python frameworks, libraries, software and resources

bdm24_mongodb_spark_example

cheshire-cat

Open source and customizable AI architecture

github-readme.md-syntax-highlighting-syntax-code-block-

Github readme.md Syntax highlighting syntax code block

grafana-mongodb-docker

Docker container for Grafana with MongoDB datasource plugin

medialpy

A small python package that allows the user to look up common medical abbreviations.

medical_abbreviations

List of medical abbreviations and their meanings

progettompa2021

Progetto MPA 2020/2021

project-aquarium

project for devOps 2020

project_radiomicclassification

Study on the classification of radiomic data radiomic data on tumour status in patients in patients with prostate carcinoma using variational autoencoder (VAE). In this project, the VAE model is used as an alternative to PCA for the selection of dataset features. Tumour classification results obtained using PCA in combination with ML models such as: KNN, SVM, Random Forest, Logit. Tumour status classification results using VAE+MPL are also processed. In addition, oversampling of the samples was carried out using the SMOTE technique (for creating new synthetic data based on the actuals), using a non-trivial target reconstruction strategy.

projectuni-cnn

Replication of research article results: Rizzo, Riccardo, et al. "A deep learning approach to DNA sequence classification." International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics. Springer, Cham, 2015.". ML models were used: Naive Bayes, SVM, Random Forest; The CNN neural network was also implemented, respecting the modifications made to the LeNet-5 network in the research article.

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