Project ,

Diabetes Prediction

In this project, you have to study the history data and find whether the patient has diabetes or not based upon their diagnosed measurements.

What will you Learn in the Project?

As part of this project, you will learn about:

  1. Data loading and Exploratory data analysis
  2. How to clean the data
  3. How to select features in the dataset to make the model accurate
  4. How to build models using machine learning algorithms like Logistic Regression, Lasso Regression and Ridge Regression
  5. ROC curves and Area Under the Curve(AUC)
  6. Model evaluation techniques using the confusion matrix, accuracy score and recall score

Tools Used

  1. Jupyter Notebook
  2. NumPy
  3. Pandas
  4. Scikit learn

Tasks Performed

This projects is divided into following high level tasks which we will be performing:

  1. Data loading and Exploratory Data Analysis
  2. Select the features in the dataset to make our model accurate
  3. Predict the model using different machine learning algorithms like logistic regression, Ridge regression and Lasso regression
  4. Perform the model evaluation using the confusion matrix, precision and recall
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Skills you will develop

Exploratory data analysis

Data cleaning

Model evaluation precision

Regression Techniques

Model evaluation

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