Table of contents
Numpy
The NumPy library is a widely used mathematics library in Python, mainly used for processing multi-dimensional arrays and matrices. It provides many functions for array operations, including array creation, indexing, slicing, broadcasting, mathematical operations, statistical analysis, etc. The NumPy library also provides many functions for array operations, such as sum, mean, median, var, etc.
The main role of the NumPy library is to provide an efficient way to process multi-dimensional arrays and matrices, making scientific computing in Python more convenient and efficient. It also provides many tools for data analysis and machine learning, such as linear algebra, Fourier transform, random number generation, etc. Therefore, the NumPy library plays an important role in the field of scientific computing in Python.
pandas
Library for data processing and analysis, especially working with tabular data.
Matplotlib
Matplotlib is a powerful, easy-to-use, flexible and diverse drawing library that is widely used in data visualization in science, engineering, finance and other fields.
Matplotlib is a Python 2D drawing library used to generate various types of graphics, such as line graphs, scatter plots, bar charts, pie charts, etc. It was originally developed by John D. Hunt and released in 2003 as part of the matplotlib.sourceforge.net website. In 2011, Matplotlib was ported to and became part of Python's NumPy library.
The main function of Matplotlib is to visualize data and the results of scientific calculations. It provides a rich set of drawing functions and options that make it easy to customize the appearance and behavior of graphics. Matplotlib also supports interactive drawing, and the display and operation of graphics can be controlled through the mouse and keyboard.
Matplotlib also supports a variety of coordinate systems, including rectangular coordinate systems, polar coordinate systems, and spherical coordinate systems. It also supports multiple data types such as arrays, matrices, tensors, etc. In addition, Matplotlib also provides many auxiliary functions and tools, such as color mapping, axis settings, legend generation, etc., to help users better understand and present data.
Seaborn
The Seaborn library is a Python visualization library based on matplotlib. It is mainly used to create various types of statistical charts and information visualization, including line charts, histograms, heat maps, scatter plots, bubble charts, violin plots, etc. Seaborn is designed to provide an easy-to-use interface that makes it easier for data scientists and analysts to create beautiful and informative charts.
Scikit-learn
Scikit-learn is a machine learning library for the Python programming language. It provides a large number of supervised and unsupervised learning algorithms, as well as functions for data processing, model selection and evaluation.
Hard
The role of the Keras library is to provide a concise and easy-to-use high-level neural network API that can quickly realize user ideas into results. It is written in Python and operates on TensorFlow, Theano and CNTK backends. Keras supports neural network structures such as CNN and RNN, and is highly modular, minimalist, and scalable, making it easy for users to conduct rapid experiments and prototyping.
OpenCV
The role of the OpenCV library is to provide many common algorithms in image processing and computer vision. It is an open source cross-platform software library that can run on operating systems such as Linux, Windows, Android and MacOS. OpenCV provides a wealth of functions, such as image reading, display, saving, conversion, filtering, edge detection, feature extraction, target detection, tracking, recognition, etc., and is widely used in various application development in the field of computer vision.
