Machine Learning / Design
Design a function to sum an array of numbers.
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Design a function that takes in an array of numbers and outputs the sum of all the numbers in the array.
Determining Linear Relationships in Data
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There are many ways to determine if there is a linear relationship between data points. Some common methods include scatter plots, correlation coefficients, and least squares regression.
Email Spam Detection using Machine Learning
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This problem asks for the design of a machine learning algorithm that can predict whether a given email is spam or not.
Designing a k-nearest neighbor classifier for two-class classification.
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The k-nearest neighbor classifier is a simple machine learning algorithm that can be used to classify data points into one of two classes, 0 or 1. The input to the classifier is a set of data points, each with two features (x1 and x2). The output of the classifier is a set of labels, each corresponding to the class (0 or 1) that the data point should be classified as.
Summing Even Numbers in a List
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Design a function that takes in a list of integers and prints out the sum of the even numbers in the list.
Detecting Plagiarism with Machine Learning
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To design a machine learning algorithm to automatically detect plagiarism, you would need to first gather a set of training data. This data would need to include a wide variety of text samples, both original and plagiarized. Once you have this data, you would then need to design a algorithm that can learn to distinguish between the two. This algorithm would need to be able to identify common patterns in the text that are indicative of plagiarism.
Implementing a k-means clustering algorithm from scratch.
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This problem asks for the implementation of a k-means clustering algorithm. The input is a dataset of points in 2D space, and the output is a set of k cluster centers .
Basic machine learning algorithm for heart attack prediction.
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This technical problem asks for the design of a machine learning algorithm to predict the likelihood of a person having a heart attack. The input data for the algorithm would include information about the person's age , weight, gender, family history of heart disease, and other relevant health data. The output of the algorithm would be a prediction of whether or not the person is likely to have a heart attack, based on the input data.
