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Total Views : 73 Underfitting : Underfitting is opposite to overfitting hence it will not work on training as well as test dataas it has not understood well. This is similar to scenario where a student gives exam with less preparation. To remove underfittingwe should give more data to the model so that it can…
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Total Views : 63 , Today Views : 1 Objective Naive Bayes is a fast, easy to understand, and highly scalable algorithm. Understand the working of Naive Bayes, its types, and use cases. Introduction Naive Bayes is one the most popular and beginner-friendly algorithms that anyone can use. In this article, we are…
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Total Views : 88 Hi Everyone, I, like most, am a Kaggle complete novice. It’s the best place to learn and develop your Data Science and Machine Learning skills through hands-on projects. Best Features of Kaggle are:- Machine Learning Competitions: This is why Kaggle is so popular. Look for problems that…
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Total Views : 138 , Today Views : 1 Lists are analogous to dynamically scaled arrays, and are declared in other languages (e.g., vector in C++ and Array List in Java). Lists do not have to be homogeneous all of the time, which makes it a very strong tool in Python. Data Types…
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Total Views : 2,038 Assignment statements in Python do not copy objects, they create bindings between a target and an object. When we use the = operator, the user can assume that we are creating a new object; however, this is not the case. It only creates a new variable which…
