Top 10 Data Science Libraries in Python.
Although there is no fixed definition of data science as no official entity is representing, data science is an interdisciplinary and vast field with a mixture of Computer science, Maths and statistic and domain knowledge which helps to extract insights, knowledge and information structural and unstructured data.
Python is one of the most popular languages used by Data Scientists to clean, process, analyze and present data is done by Python, its libraries, and framework.
This is the new revolutionary era with increasing jobs in AI and data science makes data science most demanding skill.
In this blog, line up Top 10 Data Science Libraries which are most demanding in the market.
let's start
1. NumPy
NumPy is a library for python programming language which provides a multidimensional array and tools for mathematical functions to work on the arrays.
NumPy stands for Numerical Python.
2. Pandas
Pandas is a Python library used for data manipulation and analysis. It provides highly optimized performance with fast, flexible, and expressive data structures. it is used as as a data analytics library
3. Matplotlib
Matplotlib is a popular plotting library used for static, animated, and interactive data visualization. it provides object-oriented API with cross-platform library making 2D plotted array.
4. PyTorch
Pytorch is a python open-source Machine Learning library used computer vision and NLP applications & primarily developed by Facebook’s AI Research lab.
PyTorch also has a C++ interface
5. Scipy
It is a FOSS(Free and Open Source) python library used for computing with the number of modules for statistics, technical and scientific calculations, optimization and many more.
The SciPy library under the BSD license
6. Scikit- Learn
Scikit-learn is a machine Learning python library which is free software.
Scikit-learn was formerly as scikits. learn and also called as sklearn
It was developed as a project in GSOC by David Cournapeau and built on top of other Python libraries like NumPy, SciPy, etc
7. TensorFlow
It is a popular open-source library used for numerical computation and large-scale machine learning and neural networks.
It is created and developed by Google Brain team and under Apache License 2.0
8. Keras
It is an Open Source neural network library written in python. it is a cross-platform software and capable of running on top of TensorFlow, R, PlaidMl etc.
it is majorly used for statistical data and working with images and text data over simplified deep learning.
9. Seaborn
Seaborn is a python library for Data Visualization based on Matplotlib.
It offers high-end statistical data in graphs in pictorial form.
It is used to visualize random distributions and a graphical showcase of data.
10. Beautiful Soup
beautiful soap is a python library used for data scrapping out of HTML, XML and other markup languages.
its makes it easy to get data from the web.
It is written in python and helps programmers get data easily and it's a data parser library developed by Leonard Richardson
That's all for this story now!!
Conclusion
In addition to the Top Ten Python libraries discussed here, there are many other helpful Python libraries for data science that deserve to be looked at. Share your favourites in the comments section below, as well as any interesting things about the libraries that we mentioned.
Also, there are many other pythons libraries, frameworks and we can do many things from python! Stay tuned and hit on follow button to get updated
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