EBEON1022382985-EON-DATA-ANLAYST-FINAL-PROJECT-EDUBRIGE

NAME : SAI SHIVANI VILASAGARAM
BATCH:8161-EON Advanced Certification Program in Data Analytics
Enrollment Number :EBEON1022382985

Heart plays a significant role in living organisms. Diagnosis and prediction of heart-related diseases require more precision, perfection, and correctness because a little mistake can cause fatigue problems or death of the person, there are numerous death cases related to heart and their counting is increasing exponentially day by day. To deal with the problem there is an essential need for a prediction system for awareness about diseases. Machine learning is the branch of Artificial Intelligence(AI), it provides prestigious support in predicting any kind of event which take training from natural events. In this paper, we calculate the accuracy of machine learning algorithms for predicting heart disease, this algorithm is Logistic Regression by using the Kaggle repository dataset. For the implementation of Python programming Anaconda(jupyter) Notebook is best tool, which have many type of library, header file, that make the work more accurate and precise.

• Data preprocessing
• Data Analysis
• Data Visualization
• Model Selection
• Model Training

Our Logistic Regression algorithm yields the highest accuracy, 85%. Any accuracy above 70% is considered good, but be careful because if your accuracy is extremely high, it may be too good to be true (an example of Overfitting). Thus, 85% is the ideal accuracy!