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  • February 10, 2019Blog

    What is the main difference between user based and item based collaborative filtering?

    What is the main difference between user based and item based collaborative filtering? Item based collaborative filtering finds similarity patterns between items and recommends them…

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  • February 10, 2019Helpful tips

    Can Weka handle big data?

    Can Weka handle big data? Weka allows you to do big data mining tasks like mining, processing, visualization, regression and so on based on the…

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  • February 10, 2019Miscellaneous

    What is a model in AI?

    What is a model in AI? In the simplest terms, an AI model is a tool or algorithm, which is based on a certain data…

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  • February 10, 2019Helpful tips

    What is factorization machine used for?

    What is factorization machine used for? The Factorization Machines algorithm is a general-purpose supervised learning algorithm that you can use for both classification and regression…

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  • February 10, 2019Blog

    What does random error term mean?

    What does random error term mean? The error term (also named random perturbation) is a theoretical, non observable random term responsible for the differences between…

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  • February 10, 2019Helpful tips

    What is AUC for binary classification?

    What is AUC for binary classification? The Receiver Operator Characteristic (ROC) curve is an evaluation metric for binary classification problems. The Area Under the Curve…

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  • February 10, 2019Guidelines

    What are the steps in building a machine learning model?

    What are the steps in building a machine learning model? The 7 Steps of Machine Learning 1 – Data Collection. 2 – Data Preparation. 3…

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  • February 10, 2019Guidelines

    How to solve a multi label classification problem?

    How to solve a multi label classification problem? In this method, we will try to transform our multi-label problem into single-label problem (s). This method…

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  • February 10, 2019Popular

    What are Embeddings NLP?

    What are Embeddings NLP? Word embeddings are a type of word representation that allows words with similar meaning to have a similar representation. That there…

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  • February 10, 2019Guidelines

    How HashingVectorizer works?

    How HashingVectorizer works? With HashingVectorizer, each token directly maps to a column position in a matrix, where its size is pre-defined. For example, if you…

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