As a part of the Bytewise Fellowship Machine Studying observe, I used to be assigned a venture to foretell coronary heart illness danger utilizing a dataset from Kaggle. This venture is a fruits of the talents and information I acquired through the 9 duties main as much as this venture. I want to lengthen my gratitude to my instructor, Nimra Waqar, for her steerage and efforts all through this journey.
The dataset used for this venture is the Coronary heart Illness Dataset, which may be discovered on Kaggle at https://www.kaggle.com/datasets/johnsmith88/heart-disease-dataset. This dataset comprises 14 options and 303 samples, with the goal variable being a binary classification of coronary heart illness danger.
The objective of this venture is to develop a machine studying mannequin that may predict coronary heart illness danger primarily based on the given options. The venture entails information preprocessing, characteristic scaling, mannequin coaching, and analysis.
The dataset was loaded utilizing pandas, and preliminary information data and outline have been obtained utilizing the data() and describe() capabilities, respectively. The dataset was discovered to comprise lacking values, which have been eliminated utilizing the dropna() perform.
The numerical options have been scaled utilizing the StandardScaler from scikit-learn to make sure that all options are on the identical scale.
Boxplots have been created for every numerical characteristic utilizing seaborn to visualise the distribution of the info.
A scatter plot was created to visualise the connection between the precise and predicted values.
A Linear Regression mannequin was skilled on the preprocessed information, and the efficiency was evaluated utilizing the Imply Squared Error (MSE) and R-squared metrics.
The expected values have been plotted in opposition to the precise values to visualise the efficiency of the mannequin.
On this venture, I efficiently developed a machine studying mannequin to foretell coronary heart illness danger utilizing the Coronary heart Illness Dataset. I want to thank my instructor, Nimra Waqar, and the Bytewise Fellowship for offering me with the chance to work on this venture. The abilities and information I acquired through the 9 duties main as much as this venture have been instrumental in finishing this venture.
The venture repository may be discovered on GitHub at https://github.com/Subhanahmed333/100DaysOfBytewise/blob/main/Project%201.
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