Transformative Applications of Data Science and Machine Learning: Inno-vations in Healthcare, Entertainment and Personal Finance

Abstract

Data science and machine learning have become transformative tools for addressing challenges across diverse domains. This paper presents three projects that leverage these technologies to deliver innovative solutions in healthcare, entertainment, and personal finance.  The first project focuses on heart disease prediction, utilizing machine learning algorithms to analyze key medical parameters, provide early diagnostic insights. By enabling timely interventions, this approach has the potential to significantly improve patient outcomes and alleviate the burden on healthcare systems. The second project delves into viewer analytics for the OTT platform Hotstar. Using advanced data analysis techniques, the project identifies patterns in viewer behavior, including preferences, peak viewing times, and genre popularity. These insights can be instrumental in optimizing content recommendations, enhancing user engagement, and driving business growth in the entertainment industry. The third project introduces a smart expense tracker designed to empower individuals in managing their finances. By employing predictive analytics, the tracker not only categorizes expenses but also forecasts future spending patterns, offering personalized budgeting advice and promoting financial well-being. Collectively, these projects demonstrate the versatility and impact of machine learning and data analytics in addressing real-world problems. By applying cutting-edge methodologies to distinct sectors, the work underscores the far-reaching potential of data-driven innovation in shaping a smarter, more efficient future.