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Published Date: September 29, 2018

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Pima Indians Diabetes Classification using Neural Networks in R

Learn by Coding

In this Learn Data Science by Coding – Recipe, YOU will learn:

  1. How to organise a Predictive Modelling Machine Learning project.
  2. What are the different steps in Predictive Modelling and Applied Machine Learning.
  3. How to summarise and present feature variables in Predictive Modelling (Descriptive statistics).
  4. How to visualise features through histogram, density plot, box plot and scatter matrix.
  5. How to find correlations among features variables.
  6. How to visualise target variables.
  7. How to do data analysis for feature and target variables.
  8. How to utilise CARET packages in R.
  9. How to implement Neural Networks for Binary Classification Algorithm in R.
  10. How to tune parameters: manual tuning and automatic tuning in R.
  11. How to compare Algorithms with Accuracy and Kappa using caret package in R.
  12. How save a trained model in R.
  13. How to connect to MySQL database to query prediction dataset.
  14. How to prepare prediction dataset and load a pre-trained model in R.
  15. How to make prediction using the trained model and report the result.
  16. How to complete an end-to-end Data Science Project/Recipe using MySQL and R.

Few snippets from this Data Science Recipe,

Results

Looking for Data Science Recipe?

All Data Science Recipes (Python and R codes) are found in https://setscholars.com/DataScience/productcat/data-science-recipes/

Or Simply search in Google:

a) Data Science Recipe + “name of dataset” e.g. data science recipe + iris dataset

b) Data Science Recipe + “name of dataset” + “Algorithm” e.g. data science recipe + pima diabetes dataset + random forest

Happy Coding!

  

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