Introduction
Given the recent development in the tech industry, It is quite evident that the top performing and trending fields are artificial intelligence, Machine Learning, Cloud, UI UX, Blockchain and Web3. However given the trend in 2023 with the launch of CHATGPT-4, the competition and the advancement in AI and ML is rapid.
With the launch of new AI tools and no code tools each day demand for developers that can develop these automated tools s increasing. To cater to this problem and help build more advanced tools, demand for Python is ever-growing.
Python provides various great open-source libraries that can help code better programs in a much quicker way, providing more flexibility and scope of scaling applications faster to the companies.
In this Blog Post, I will discuss the 9 - Top Python Libraries that can be of extreme use while developing applications in Python
So let's get started......
What Exactly is a Library?
It is a collection of utility methods, classes, and modules that we can use to code our application to perform specific tasks without writing the functionalities from scratch. A library is nothing more than a list of class definitions.
We mainly use libraries for the sole purpose of Code reusability. Meaning we use the code that has already been produced or written down by other people for our purpose.
Libraries Play a crucial role programmers' life, as they prevent programmers from reinventing the wheel again and again while focusing on the real problem.
9 - Top Python Libraries
Here is the list of 9-Top libraries in Python
Pandas
Numpy
Keras
TensorFlow
Scikit Learn
Eli5
Scipy
Pytorch
Theano
Pandas
It is a high-level building block for doing practical, real-world data analysis in Python. Pandas is widely used in the field of data science. It is for data analysis, manipulation, cleaning, etc. Pandas allow for simple data modeling and data analysis operations
Numpy
NumPy is an open-source project that enables numerical computing with Python. It has built-in mathematical functions for quick computation that support multi-dimensional big data computation.
Keras
Keras is a deep-learning API written in Python. It runs on top of the machine learning platform TensorFlow. It was developed with a focus on enabling fast experimentation. Keras is Simple, Flexible & Powerful that is used by organizations and companies including NASA, YouTube, or Waymo.
TensorFlow
TensorFlow makes it easy for beginners and experts to create machine learning models for desktop, mobile, web, and cloud. It is currently widely utilized by math, physics, and machine learning researchers for complicated mathematical computations.
Scikit Learn
Scikit Learn is an open-source library for machine learning algorithms. It is built on Python and it provides simple and efficient tools for predictive analysis. It is built on NumPy, SciPy & Matplotlib. It is used by Music Platform Spotify for Music Suggestions. It is used in machine Learning and perform data Mining Tasks.
Eli5
ELI5 is a Python package that helps to debug machine learning classifiers and explain their predictions. Eli5 provides support to many machine learning frameworks and packages such as scikit-learn, Keras, XGBoost, LightGBM, CatBoost, lightning, sklearn-crfsuite etc
SciPy
SciPy provides algorithms for optimization, integration, interpolation, eigenvalue problems, algebraic equations, differential equations, statistics and many other classes of problems. It wraps highly-optimized implementations written in low-level languages like Fortran, C, and C++. SciPy's high-level syntax makes it accessible and productive for programmers
Pytorch
PyTorch is an optimized tensor library for deep learning using GPUs and CPUs. PyTorch is mostly used for natural language processing applications.
Theano
It is a Python library that allows you to define, optimize, and efficiently evaluate mathematical expressions involving multi-dimensional arrays. Theano makes it possible to quickly implement code because of its rich library. Unstable expressions can be recognized and computed, making this library more useful over NumPy.
Conclusion
Python code being easy-to-use, it has found its widespread use in real-world applications. Thanks to the various high-end libraries that can be used to save time coding in Python. Using these Libraries programmers can perform various tasks without having to code from scratch.
Thank you if you read this post and have found this post useful. I hope you have a great read and are enjoying my magical journey of Python coding. This is it for this Blog Post
See you in the next one.....
About Me
Hey Guys, I am Chintan Jain from CodeWithJain. I am a trader and content creator. I am also passionate about tech and hence wanted to explore the field of tech. I always wanted to learn to code so I watched many tutorials but procrastinated practicing coding. To get into the habit of coding consistently I am starting to BLOG with HASHNODE on daily basis.
I will document my coding journey from scratch and share my daily learnings in a blog post on HASHNODE. I hope you all will enjoy my content and my coding journey.
So what are you waiting for, smash the FOLLOW and LIKE buttons and follow along my coding journey, a step to create more beautiful digital products and empower people.