Python is often used as the programming language of choice for developers who need to apply statistical or data analysis techniques in their work. Python is also the programming language used by Data Scientists to create various types of Machine Learning models. Python has really become a popular language in the Machine Learning field. The combination of consistent syntax, shorter development times, and flexibility makes Python well-suited for developing advanced machine learning computer vision models and predictive engines that can be connected directly to production systems.
One of Python’s greatest assets is its extensive library. A library is a collection of routines and functions written in a particular language. A robust collection of libraries can make it easier for developers to perform complex tasks without the need to rewrite many lines of code. Most Machine Learning models are based on mathematics. In particular, optimization of mathematics, statistics and probability. Python libraries help researchers/mathematicians with less developer knowledge to easily create Machine Learning models.
NumPy stands for Numerical Python. In simple terms, Numpy contains a collection of mathematical calculations that will speed up Data Scientists and Developers when they want to do some fairly complex mathematical calculations. Python also contains a general-purpose array processing package. The large collection of high-complexity mathematical functions makes NumPy powerful for processing large multi-dimensional arrays and matrices. NumPy is very useful for dealing with linear algebra, Fourier transforms, and random numbers. Other libraries like TensorFlow use NumPy on the backend to manipulate tensors. With NumPy, we can define arbitrary data types and easily integrate with most databases. NumPy can also serve as an efficient multi-dimensional container for any common data that exists in any data type. Numpy will be very essential because it becomes the basis and foundation for several other libraries such as Pandas, Matplotlib, Tensorflow, and so on.