About Useful Python Tools

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About Useful Python Tools

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About Useful Python Tools

• Among the developers, Python is one of the most
  popular languages in todays world. There are
  numerous reasons behind the popularity of Python
  but primarily two reasons are easy syntax writing
  and an exclusive range of libraries, tools for
  data science, and scientific computing that
  Python offers to its users.
• Today, we will discuss the most widely used
  Python tools by data scientists and developers
  across the world. If you know how to use them
  then these tools are very convenient for many
  different purposes.

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Lets divide these tools into some Categories
that are mentioned below

• Data Science Python tools
• Keras
• Scikit learn
• Theano
• SciPy
• Automation Testing Python tools
• Selenium
• Robot Framework
• TestComplete
• Web SLXML
• Scrapy
• Urllib
• craping Python tools

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Data Science Python Tools

1. Keras - Keras is an open-source, high-level
   neural network API written in Python. It supports
   multiple back-ends, neural network models. It is
   highly convenient for Machine Learning and Deep
   Learning field. Keras library is user-friendly,
   easy to extend, modular, and working with Python.
   It is easy to introduce your new neural network
   with the help of modules that Keras provides like
   neural layers, activation function, cost
   functions, optimizer, etc. Kears supports a wide
   range of production deployment, integration with
   back-end engines like Tensorflow, CNTK, Theano,
   LXNet, and PlaidML.

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Scikit learn

• It is an open-source for data science and machine
  learning used by developers and data scientists
  for data mining and predictive data analysis
  operations including classification, regression,
  clustering, and dimensionality reduction. It
  includes features like supervised learning
  algorithm (Support Vector Machines (SVM),
  Decision Trees to Bayesian methods ),
  cross-validation, unsupervised learning algorithm
  clustering, factor analysis, principal component
  analysis to unsupervised neural networks, feature
  extraction, and a lot of more.

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Theano

• Theano is a completely Python-based library that
  allows optimizing, defining and evaluating any
  mathematical expressions of the multidimensional
  array in a very efficient way. Some key features
  that make this library very efficient are
  integration with NumPy, transparent use of GPU,
  allow efficient symbolic differentiation,
  stability optimization, speed, and expensive unit
  testing.

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Scipy

• It is an open-source library ecosystem used for
  technical and scientific computing. Engineering,
  Science, and mathematics is the main domain in
  which this library is extensively used. It
  leverages other Python packages, including
  pandas, ipython, and NumPy to make it more
  general for science and math-oriented programming
  tasks.

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Web Scraping Tools

• Beautiful SoupThis Python library is used to
  pull data from HTML and XML files. Some key
  features of beautiful soup are It provides a few
  simple functions and pythonic idioms for
  searching, navigating, and modifying the
  parse-tree. It converts incoming documents to
  Unicode and outgoing documents to UTF-8
  automatically. It works on top of Python parsers
  like html5lib and lxml for different parsing
  strategies and flexibility.
• LXMLIt is the most easy-to-use library for
  processing HTML and XML in Python. The key
  features of this library are its extremely fast
  while parsing a large document, well documented,
  and easy conversion of data into Python data
  types, easier file manipulation.

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• Scrapy
• Its an open-source Python library used for
  developing web spiders that crawl websites and
  extract data from them. Scrapy is a fast web
  crawling and scraping framework used for many
  tasks like data mining and automated testing.
• Urllib
• This Python module is designed for collecting and
  opening URLs. It has many functions to work with
  URLs. It uses urllib.request for opening and
  reading url most of the time it is HTTP,
  urllib.error for defining the exception class
  for exceptions that are raised by
  urllib.request, urllib.parse used to define a
  standard interface to fragment URL string.

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Online Python Certificate Exam

• Python For Big Data Certification
  Exam(Foundation)
• Python Certification Exam (Foundation)
• Python Certification Exam (Advanced)
• Python Expert Certification Exam
• Blockchain Python Developer Certification
  Exam(Foundation)
• Blockchain Python Developer Certification
  Exam(Advanced)
• Blockchain Python Developer Certification
  Exam(Expert)

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