Python is one of the most popular and widely known programming languages that has replaced many programming languages in the industry.
It is one of the most loved programming languages that data science professionals use more because it is an ocean of libraries.
Python is known as the beginner’s level programming language because of its simplicity and easiness, its programming syntax is simple to learn and is of high level compared to C, Java, and C++.
For more accurate algorithms and coding, Analytics Insight compiles the top 10 Python libraries, here is the list.
Pytorch is an open source library, it basically a replacement of Numpy. PyTorch comes with higher-level functionality useful for building a deep neural network. Data Science professionals still can use other languages such as scipy, Cython, and numpy which help to extend PyTorch when required. Pytorch is used by many organizations including Facebook, Twitter, Nvidia, Uber for rapid prototyping in research and to train deep learning models.
Arrow is a human-friendly Python library which offers features like manipulating, creating and formatting converting dates, times, and timestamps. It supports Python 2 and 3 and it is an alternative of DateTime facilitating rich features with a nicer interface.
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This is one of the most useful python tools, offering a rich architecture to it user. With IPython, users can write and execute python codes in their browser. Ipython works on several operating systems including Windows, Mac OS X, Linux and most other Unix OS. Ipython lets users more functions that include help function, advanced editing etc.
Tensor flow is an open-source machine learning python library created by the Google Brain Team. Tensor flow library is used to develop, train and design deep learning models, and can be used to do numerical computations. Tensor flow is an alternative of Theano, which can run on mobile devices, single CPU system and on GPU too.
Caffe2 is the attempt to bring Caffe framework to the modern world. It supports distributed training, deployment even in mobile platforms. While PyTorch may be better for research, Caffe2 is suitable for large scale deployments as seen on Facebook.
Scrappy is a widely used Python web scraping library. Scrappy is used for creating crawling programs, initially, ands was designed for scraping, like its name indicates. Now it used for multiple purposes that include data mining, automated testing, etc. scrapy is open-source and must have library.
Requests is one of the famous Python libraries which is licensed under Apache2 and written in Python. This library helps users to interact with multiple languages. With Request library, users can string manually to their URL’s. They can send HTTP request to server using Request library and can add form data, content like header, multi-part files, etc.[…]