Machine Learning

Numpy Tutorials [beginners to Intermediate]

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This is a full NumPy tutorial for beginners. This NumPy tutorial covers almost all the basics to get started with NumPy. You will find all the key points explained with respective python code which will help to understand this NumPy tutorial better. This is full numpy tutorial."

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Basic concepts of (K-Nearest Neighbour)KNN Algorithm

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It is probably, one of the simplest but strong supervised learning algorithms used for classification as well regression purposes. It is most commonly used to classify the data points that are separated into several classes, in order to make predictions for new sample data points. It is a non-parametric and lazy learning algorithm. It classifies the data points based on the similarity measure (e.g. distance measures, mostly Euclidean distance)." " "

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Implementation Of KNN (From Scratch in PYTHON)

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KNN classifier is one of the simplest but strong supervised machine learning algorithms. It can be used for both classification and regression problems. There are some libraries in python to implement KNN, which allows a programmer to make a KNN model easily without using deep ideas of mathematics. But if we try to implement KNN from scratch it becomes a bit tricky." " "

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Implementation Of KNN(using Scikit learn,numpy and pandas)

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If we try to implement KNN from scratch it becomes a bit tricky however, there are some libraries like sklearn in python, that allows a programmer to make a KNN model easily without using deep ideas of mathematics. "

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Understanding K-Nearest Neighbor Algorithm (With Examples)

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In this article, you will understand the basics of the KNN algorithm and learn how to implement KNN from scratch and using a python library Sklearn" "

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