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Data scientists looking for their first machine learning or data science project begin by trying the handwritten digit recognition problem. The Digit Recognizer data science project makes use of the popular MNIST database of handwritten digits, taken from American Census Bureau employees. The dataset consists of already pre-processed and formatted 60,000 images of 28x28 pixel handwritten digits. With the use of image recognition techniques and a chosen machine learning algorithm, a program can be built to accurately read the handwritten digits with 95% accuracy. The accuracy rate can be higher based on the chosen machine learning algorithm,
Build a predictive model to correctly classify products between 9 product categories (fashion, electronics, etc.) using the Otto Group dataset.
In this data science project, you will contextualize customer data and predict the likelihood a customer will stay at 100 different hotel groups.
In this project, we will automate the loan eligibility process (real-time) based on customer details while filling the online application form.