External Packages (page 8 of 38)

With numpy, we can perform a variety of descriptive statistics (e.g., mean, median, model, and standard deviation) along the different dimensions (e.g., rows, columns, and frames) in our numpy arrays. We can efficiently perform trigonometry calculations using our numpy arrays, but traditional business problems typically do not require trigonometry. Numpy arrays can also be used for matrix algebra, which is beneficial for neural networks. Due to the efficiency of numpy arrays, numpy arrays often serve as the base data structure for methods in other packages such as scipy and sklearn.