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Hyperparameter Search With Optuna: Part 3 – Keras (CNN) Classification and Ensembling

by GCBC Ventures | Feb 19, 2020 | Machine Learning

Hyperparameter Search With Optuna: Part 1 – Scikit-learn Classification and Ensembling Hyperparameter Search With Optuna: Part 2 – XGBoost Classification and Ensembling Introduction Using Optuna With Keras Results Code 1. Introduction In this article, we use the...

Hyperparameter Search With Bayesian Optimization for Keras (CNN) Classification and Ensembling

by GCBC Ventures | Feb 10, 2020 | Machine Learning

Introduction Using Bayesian Optimization Ensembling and Results Code 1. Introduction In this article we use the Bayesian Optimization (BO) package to determine hyperparameters for a 2D convolutional neural network classifier with Keras. 2. Using Bayesian Optimization...

Prediction of Small Molecule Lipophilicity: Part 5 – Ensemble of 2D Convolutional Neural Networks With Morgan (Circular) Fingerprints

by GCBC Ventures | Jan 12, 2020 | Cheminformatics, Machine Learning

Previous articles in this series: Prediction of Small Molecule Lipophilicity: Part 1 – Data Exploration Prediction of Small Molecule Lipophilicity: Part 2 – TPOT (Tree-based Pipeline Optimization Tool) With Morgan (Circular) Fingerprints Prediction of Small Molecule...

Prediction of Small Molecule Lipophilicity: Part 4 – Ensemble of 1D Convolutional Neural Networks With Morgan (Circular) Fingerprints

by GCBC Ventures | Jan 7, 2020 | Cheminformatics, Machine Learning

Previous articles in this series: Prediction of Small Molecule Lipophilicity: Part 1 – Data Exploration Prediction of Small Molecule Lipophilicity: Part 2 – TPOT (Tree-based Pipeline Optimization Tool) With Morgan (Circular) Fingerprints Prediction of Small Molecule...

Peptide Binding – Part 1: 1D Convolutional Neural Network

by GCBC Ventures | Sep 29, 2019 | Bioinformatics, Machine Learning

Introduction Data Simple 1D CNN Simple 1D CNN With Cross Validation And Early Stopping Code 1. Introduction In Deep Learning for Cancer Immunotherapy, Leon Eyrich Jessen used various machine learning algorithms to classify peptide binding strength into three classes,...

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