1. An automobile dealership wants to use historic car sales data to train a machine learning model. The model should predict the price of a pre-owned car based on its make, model, engine size, and mileage. What kind of machine learning model should the dealership use automated machine learning to create? ClassificationRegressionTime series forecasting

2. A bank wants to use historic loan repayment records to categorize loan applications as low-risk or high-risk based on characteristics like the loan amount, the income of the borrower, and the loan period. What kind of machine learning model should the bank use automated machine learning to create? ClassificationRegressionTime series forecasting

A data scientist is trying to create a Neural Network that can predict and successfully trade stock prices based sole on its previous prices and/or reported financial metrics. What type of deep learning systems would be best suited for her purpose?AUse a generic artificial neural network ANNBUse a convolutional neural network CNNCUse a recurrent neural network RNNDUse a forward propagation neural network FNN

A data scientist is trying to create a Neural Network that can predict and successfully trade stock prices based sole on its previous prices and/or reported financial metrics. What type of deep learning systems would be best suited for her purpose?

In which of the following areas is machine learning commonly applied?Answer areaMedical diagnosisStock market predictionSpeech recognitionAll of the above

An online retailer uses a smart analytics tool to ingest real-time customer behavior data to surface the best suggestions for particular users. How can machine learning guide this activity?Machine learning can help identify user behavior in real time, but cannot make personalized suggestions based on the data.Machine learning can be used to make all users see the same product recommendations, regardless of their preferences or behavior.Through machine learning, with every click that the user makes, their website experience becomes increasingly personalized.Through machine learning, a user’s credit card transactions can be analyzed to determine regular purchases.