Programming skills are a must in the software space, as they help create unique, tailored solutions for different business requirements. These are highly valued across all industries, and companies of all scales and sizes are in constant need of tech-savvy professionals.
Are you looking to enhance your programming skills and learn the latest relevant technologies?
Education Nest can help you with the best professional courses curated specifically for corporate growth and excellence. It is a leading global knowledge exchange platform committed to delivering clear, measurable results.
Python is one of the most in-demand programming languages. It has grown over three decades, and there are no signs of slowing. It is beginner-friendly, flexible, and offers versatile development solutions. As per recent reports, about 66% of developers like to work in Python.
One of the main reasons for Python’s growing popularity is its wealth of libraries. These libraries can be linked with the program to extract different functionalities. They provide already built-in crucial codes that can be repeatedly used for different projects. It saves considerable time and effort as you do not need to write the program from scratch.
So, what are the top Python libraries every developer should know? Read on to find out.
Top 10 Python Libraries
If you want to excel in Python, then you must have a very good understanding of Python libraries. It helps perform a wide variety of operations, thus making your tasks easier and simpler.
Here are the top 10 Python libraries that you should know as a developer:
NumPy
NumPy, or Numerical Python, is a fundamental library that supports scientific computing. It is an open-source project that provides a wide range of mathematical functions for performing complex calculations.
Features:
- Powerful N-dimensional arrays
- Developed and maintained publicly on GitHub
- Interoperable, fast, and versatile with well-optimized C code
Uses: Mathematical and statistical computations, Numerical simulations and modeling Supports data structures and other libraries
Pandas
The AQR Capital Management developed the Pandas Library in 2008. It was open-sourced within just a year. This Python library extensively supports the data science ecosystem with its eloquent syntax and rich functionalities.
Features:
- Intelligent data alignment, data cleansing, and processing
- Fundamental high-level building block for data analysis and modeling
- Cython or C-based critical code paths for optimal performance
Uses: ETL (Extract, Transform, Load) operations, Open-source data analysis and manipulation, Structured data handling
TensorFlow
Developed by Google, this open-source library is specifically helpful for Artificial Intelligence and Machine Learning applications. TensorFlow is a powerful deep-learning framework, largely preferred for high-level operations involving complex computations.
Features:
- Straightforward and simple syntax
- Highly flexible architecture and allows customized functions and services
- Interactive code samples with quick updates
Uses: Speech/image recognition, Computational graphs visualization, Predictive analysis, Text-based applications
MatPlotLib
This library in Python is extensively used in data science applications because of its versatile plotting capabilities. MatPlotLib is a powerful tool that helps create interactive visualizations for easy interpretation.
Features:
- Customizable visual styles and layouts
- Highly adaptable and easy-to-use navigation system
- Rich features with a range of personalization options
Uses: Publication-quality plots, High-defined charts, graphs, scatterplots, and more, Business Analytics, Static and interactive animations
Scikit-learn
Scikit-learn is also a popular Python library that supports advanced Machine Learning applications. It was developed using the NumPy, SciPy, and MatPlotLib libraries and is widely used for predictive data analysis.
Features:
- Consistent API for easy learning and usability
- Wide range of supervised and unsupervised learning algorithms
- Simple and efficient tools for data mining and analysis
Uses: Spam detection, Image recognition, Building predictive models, Pamareter tuning, Feature extraction and normalization
OpenCV
This Python library is used for advanced computer vision tasks. OpenCV is free for commercial use and aims to increase the use of machine perception in real-time applications.
Features:
- Over 2500 advanced algorithms for Computer Vision solutions
- Impressive real-time processing abilities
- Cross-platform support and works on Linux, IOS, Android, MacOS, Windows
Uses: Object Detection, Video Processing, Photogrammetry,
Keras
Keras is a highly productive Python library designed for humans. Its simple and consistent interface makes it a top choice even for beginners and reduces cognitive load.
Features:
- Highly productive interface enabling fast experimentation
- Clear and actionable error messages
- Great documentation and developer guides
Uses: Building and training AI models, Prediction, Feature Extraction, Neural Networks Implementation
Read More
9 KPIs to Measure the Success of Your Digital Marketing Campaigns
A Beginner’s Guide to Employee Development Strategies
Flask
This Python library helps in building web applications and services. Flask follows a minimalist approach and supports modular programming, making it easier to create basic solutions with minimal dependencies.
Features:
- Highly flexible framework with extensions for more functionalities
- Great for small and medium-scale projects
- Easy-to-learn, extensive documentation, and support
Uses: Web development, Creating RESTful APIs, Prototyping, Designing Minimum Value Products
PyBrain
PyBrain library is ideal for developers starting off with Artificial Intelligence and Machine Learning. It has easy-to-use algorithms that make it easier to customize, experiment, and validate performance.
Features:
- Supports supervised and unsupervised learning models
- Extensive tools for classification, regression, clustering, and other functions
- Backs up a range of neural network architectures
Uses: Natural Language Processing, Machine Learning Applications, Reinforcement learning, Research and Analysis
Seaborn
Seaborn is a Python library that is widely used for data visualization. It has a concise syntax and is based on the MatPlotLib. It can also be integrated with Pandas for better data manipulation and simultaneous visualization.
Features:
- Intuitive APIs and user-friendly interface
- Advanced plotting functions for better interpretation
- Built-in themes and aesthetics for better visual appeal
Uses: Informative statistical graphics, Exploratory Data Analysis, dashboard visuals, Data Science and Machine Learning tasks
Wrapping Up
Python has more than 1,37,000 libraries, and the number is continuously growing. It shows how powerful this language is. Since Python is used across almost all real-world technical applications, it is the right time to unlock its full potential and explore endless possibilities.
So, equip yourself with top-notch corporate training solutions from Education Nest. With years of experience and expertise, our seasoned industry experts ensure the best enterprise learning pathway to reach your desired goals.
For more details, reach out to us today.
