Results-oriented Information Technology postgraduate with a strong academic foundation in Data Science and practical experience building machine learning solutions using Python. Passionate about Data Analytics, Artificia…
Results-oriented Information Technology postgraduate with a strong academic foundation in Data Science and practical experience building machine learning solutions using Python. Passionate about Data Analytics, Artificial Intelligence, and Software Development. Recognized for analytical thinking, continuous learning, and the ability to transform raw data into meaningful insights. Currently seeking internship opportunities to contribute to innovative projects while developing industry expertise.
<p>Lung Cancer Prediction Using Random Forest Classifier</p><p></p><p>Lung Cancer Prediction using Random Forest Classifier is highly important in the medical field as it enables early detection and accurate diagnosis of one of the most deadly diseases worldwide. By analyzing large sets of patient data such as age, smoking history, genetic factors, and imaging results, the Random Forest model can identify complex patterns and predict the likelihood of cancer with high accuracy. Its ensemble approach reduces errors and improves reliability compared to single-model predictions.</p><p></p><p>It Mainly Focuses on:-</p><p></p><p>• Worked on a machine learning project focused on predicting lung cancer risk using patient-related data</p><p></p><p>• Handled data cleaning, feature selection, and model training using Python</p><p></p><p>• Gained practical understanding of how ML models can support healthcare decision-making</p>
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