This problem is about using machine learning to detect human faces in images. The data set consists of images, and the task is to classify them into two categories: those that contain a human face , and those that do not.
Supervised learning is a type of machine learning that involves using a labeled training dataset to develop a model that can predict the label for new data.
This problem is a supervised learning problem where the goal is to predict the label of a point in 10 dimensions, given a dataset of 100,000 points with labels.
The k-nearest neighbors algorithm is a supervised learning algorithm that can be used for both classification and regression. The algorithm works by finding the k nearest neighbors to a given data point, and then using those neighbors to predict the class or value of the data point.
This problem deals with finding a mathematical function that best describes the relationship between variables in a given set of data points. This is important in machine learning and data science in order to build accurate models .