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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:
- How to organise a Predictive Modelling Machine Learning project.
- What are the different steps in Predictive Modelling and Applied Machine Learning.
- How to summarise and present feature variables in Predictive Modelling (Descriptive statistics).
- How to visualise features through histogram, density plot, box plot and scatter matrix.
- How to find correlations among features variables.
- How to visualise target variables.
- How to do data analysis for feature and target variables.
- How to utilise CARET packages in R.
- How to implement Neural Networks for Binary Classification Algorithm in R.
- How to tune parameters: manual tuning and automatic tuning in R.
- How to compare Algorithms with Accuracy and Kappa using caret package in R.
- How save a trained model in R.
- How to connect to MySQL database to query prediction dataset.
- How to prepare prediction dataset and load a pre-trained model in R.
- How to make prediction using the trained model and report the result.
- How to complete an end-to-end Data Science Project/Recipe using MySQL and R.
Few snippets from this Data Science Recipe,
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a) Data Science Recipe + “name of dataset” e.g. data science recipe + iris dataset
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