Parallel computing in Python using Dask

Parallel computing is an architecture in which several processors execute or process an application or computation simultaneously. Parallel computing helps in performing extensive calculations by dividing the workload between more than one processor, all of which work through the calculation at the same time. The primary goal of parallel computing is to increase available computation power for faster application processing and problem solving. In sequential computing, all the instructions run one after another without overlapping, whereas in parallel computing instructions run in parallel to complete the given task faster. Dask is a free and open-source library used to achieve parallel computing in Python. It works well with all the popular Python libraries like Pandas, Numpy, scikit-learns, etc.