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I have a dataframe that contains product and in this dataframe I have some features like: brand, cat1, cat2, cat3, city, desc, image_count, mileage, price, title, year. The goal is predicting category of products. I have 1 billion training data and important features for prediction are title and description that are text type. I like to know what algorithm is best for my prediction? I'm a beginner in machine learning and confused among different algorithms. Thanks

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  • $\begingroup$ If you share some data we can come to a better answer for your problem. $\endgroup$ – JahKnows Feb 17 '19 at 17:30
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This seems like an ideal problem for deep learning. Your outputs will be the categories and you can pick the 3 activations (categories) with the highest probabilities.

You will need to vectorize your description features, you can do this using one of these techniques.

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