Protein encodings

In order to use protein sequences as inputs for deep learning models they need to be transformed into numerical descriptors. In this notebook I highlight four different ways to generate such numerical features from protein sequences.

Predicting Titanic passenger survival using tidymodels

In this post I explain how I build and tuned a Machine Learning model in R using the tidymodels package to predict passenger survival on the Titanic. I define some new features from the data to enhance the accuracy of the model and perform tuning of the model in Python using optuna. The final model reaches a top 2% score on Kaggle.

Optuna Samplers

An important step in building ML models is choosing a set of optimal hyperparameters. One of the best python packages to tune hyperparameters is Optuna. In this article I use Optuna to estimate the minimum and maximum of a simple function and try to illustrate, with a set of interactive graphs, what makes Optuna so efficient.

Editable DataTables in R shiny using SQL

This tutorial describes how to make a DataTable in Shiny with Add, Edit, Copy and Delete functionality. Entries are stored in a local SQL database which makes it possible to retrieve the data between sessions.

By Niels van der Velden in R RSQLite

August 14, 2019