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General:  ml pipelines Type:  dataset Task:  classification Data Domain:  tabular Framework:  scikit-learn Integration:  git github
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master-merge
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catboost, flaml
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Bug removed, pipeline completed
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Update LICENSE
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Update README.md
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Bug removed, pipeline completed
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6821f7a5df
Bug removed, pipeline completed
2 years ago
6821f7a5df
Bug removed, pipeline completed
2 years ago
6821f7a5df
Bug removed, pipeline completed
2 years ago
6821f7a5df
Bug removed, pipeline completed
2 years ago
6821f7a5df
Bug removed, pipeline completed
2 years ago
f10057abb7
catboost, flaml
2 years ago
f10057abb7
catboost, flaml
2 years ago
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Update load-data.py
2 years ago
6821f7a5df
Bug removed, pipeline completed
2 years ago
6821f7a5df
Bug removed, pipeline completed
2 years ago
6821f7a5df
Bug removed, pipeline completed
2 years ago
6821f7a5df
Bug removed, pipeline completed
2 years ago
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README.md

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Covid19 Vaccine Epitope Prediction ML Pipeline Using Orchest

image Image by Author | Elements by Vecteezy

Designing your first machine learning pipeline with few lines of codes and simple drag & drop using Orchest. You will learn to preprocess the data, train the machine learning model, and eventually evaluate the results. In this project we will train binary classification model to predict epitope which is used for vaccine development.

orchest

Data

Kaggle

We are going to utilize SARS-CoV and B-cell datasets to classify peptides into two categories, antibodies with inducing properties are labeled as positive (1) and antibodies without inducing properties are labeled as negative(0). To learn more about the dataset read the research paper.

ML Pipeline

image

Results

image

ko-fi

Tip!

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About

Designing your first machine learning pipeline with few lines of codes and simple drag and drop using Orchest. In this project we will train binary classification model to predict epitope which is used for vaccine development.

Collaborators 1

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