K-fold cross validation

The greatest headache for any machine learning engineer is the problem of overfitting. The model we trained works perfectly on the training dataset but when applied to other new dataset it fails miserably. This is because of overfitting where our classifier learns the provided dataset accurately but fails when applied on new data. One good …

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Converting Color Images to Grayscale using numpy and some Mathematics

An extremely magnified image at the end is just blocks of colors called pixels, where each pixel is formed by the combination of Red, Blue and Green, our primary colors. RGB color space or RGB color system, constructs all the colors from the combination of the intensities of Red, Green and Blue colors. The red, green and …

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Mathematics of Principal component analysis

Principal component analysis is a method used to reduce the number of dimensions in a dataset without losing much information. It’s used in many fields such as face recognition and image compression, and is a common technique for finding patterns in data and also in the visualization of higher dimensional data. PCA is all about …

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Understanding the Classification report through sklearn

A Classification report is used to measure the quality of predictions from a classification algorithm. How many predictions are True and how many are False. More specifically, True Positives, False Positives, True negatives and False Negatives are used to predict the metrics of a classification report as shown below. The report is copied from our previous …

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