Heart Disease Classification Using Machine Learning

Heart Disease Classification Using Machine Learning Techniques including Logistic Regression, KNN, Naive Bayes Classification, Support Vector, Decision Tree and Random Forest Classification

Advanced 5(1 Ratings) 107 Students enrolled English
Created by Karan Arora
Last updated Tue, 06-Jun-2023
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Course overview

Heart disease is one of the Leading reason for death around the world. In which machine learningis a method that predicts the emerging prospects of Heart Disease. Machine learning is used in taking care of numerous issues in information science. The basic utilization of machine learning is the forecast of a result dependent on already existing information. The machine takes the designs from the current dataset, and it is applied on an obscure dataset to foresee the result. Order method in AI is usually used for expectation. Some arrangement calculations foresee with acceptable precision, while others show a restricted exactness. Here, we play out an order dependent on various arrangement calculations like K-Nearest Neighbour, Support Vector Machine, Naïve Bayes, logistic regression, decision tree algorithm and random forest algorithm

What will i learn?

Requirements
  • python
  • scikit learn
  • data science
  • machine learning
Curriculum for this course
3 Lessons 00:00:00 Hours
Classification Project
1 Lessons 00:00:00 Hours
  • Heart Disease Classification using Scikit-Learn
    .
Download
2 Lessons 00:00:00 Hours
  • Download Jupyter Notebook
    .
  • Download Dataset
    .
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Karan Arora

25 Reviews | 1430 Students | 43 Courses
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