![]() Banking Problem – A classification problem that predicts consumer behavior based on various features using machine learning models.Stock Market Analysis – Using historical stock market data, you will learn about how feature engineering and feature selection can provide you with some really helpful and actionable insights for specific stocks.Object Detection – A much more advanced yet simple case study that will guide you toward making a machine learning model that can detect objects in real-time. ![]() Housing – This real estate case study will guide you towards real world problems, where a culmination of multiple features will guide you towards creating a predictive model to predict housing prices.Census – Using predictive modeling techniques on the census data, you will be able to create actionable insights for a given population and create machine learning models that will predict or classify various features like total population, user income, etc.Rating Predictions – This text classification and sentiment analysis case study will guide you towards working with text data and building efficient machine learning models that can predict ratings, sentiments, etc.Recommendation Engine – The case study will guide you through various processes and techniques in machine learning to build a recommendation engine that can be used for movie recommendations, restaurant recommendations, book recommendations, etc.r2, adjusted r2, mean squared error, etc.Confusion matrix – To evaluate the true positive/negative, and false positive/negative outcomes in the model. ![]()
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