One Pager Cheat Sheet

• The Euclidean Distance is the shortest distance between two points, typically used to calculate the distance between two rows of numeric values such as floating point or integer values.
• The Pythagorean Theorem can be used to compute the Euclidean Distance between two points, or two sets of coordinates, by calculating the square root of the sum of their squared differences.
• The Euclidean distance between two points in a two-dimensional space can be calculated using the Pythagorean Theorem formula √[(x2-x1)² + (y2-y1)²].
• The formula to find the Euclidean distance between two points of 3 Dimensions is merely the addition of their respective coordinates, calculated by the euclidean_distance function.
• The Euclidean distance between the points P(3,6,1) and Q(4,1,5) is calculated using the formula √[(x2-x1)² + (y2-y1)² + (z2-z1)²], which results in a distance of 6.5.
• Euclidean Distance is a widely used distance measure in Machine Learning, which is essential for many popular algorithms like k-nearest neighbors and k-means clustering.