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Top 10 Popular Python Libraries for 2022 - Popular Python Packages

Top 10 Popular Python Libraries for 2022 - Popular Python Packages

In this article we will talk about the top 10 most popular Python libraries that every developer should know; Python is undoubtedly the best programming language in the world based on the number of users or based on the number of areas that Python is being used. So it is considered one of the primary languages for every developer and organization. So Python is famous because one of the reasons is it is open-source. And the other thing is it has an extensive package library, where everyone can contribute to Python packages and create their own. So yeah, in this video, I will talk about the top 10 Python packages that one should know; let's get started.

1. TensorFlow

TensorFlow is undoubtedly the top Python package used in machine learning and deep learning. So if you're building a neural network and working on building a vast machine learning application, then ultimately, TensorFlow is the best option to go for. So TensorFlow has an extensive range of options to choose from when building a machine learning model. So it is used to handle a neural network intensively without any data problems. So it is still considered as one of the best packages in 2021 to go for. 

2. NumPy

NumPy stands for Numerical Python. So if you're someone who's starting your career in data analytics, then you might have heard this term called NumPy. So NumPy makes your mathematic in Python very easy. So if you're performing something on the data analytics or machine learning side you need to achieve, you need to understand mathematics in a pervasive way. So you need Linear Algebra, Unit statistics, you need everything. But what NumPy does is n bits, every mathematical function as a Python function, so you can use some Python functions to perform all those mathematical operations very quickly. So NumPy is one of the best Python packages to go for when you are looking to start your career in data analytics. 

3. Pandas

Pandas is one of the popular Python packages used to handle and manage data. So if you're working in a data in data side, and you are working on CSV files or Excel files, then you need the pandas mandatory because Python because pandas is a compulsory Python package to handle any data. So you can claim the data, and you can organize the data in a CSV file. So you can import the columns from the CSV file, manage that, and make some analytics out of the data set you have. So yeah, the panda is a convenient package that one can use to get insights and analytics about the data sets. 

4. PyTorch

PyTorch is an alternative to tensor flow that one can use. So pie torch is being developed by Facebook and is primarily used by Facebook. So it also performs the same operations that TensorFlow does. So it is mainly helpful in dealing with neural networks and all those stuff. So yeah, if you're someone who is very much fancy about building a machine learning model with advanced neural nets, then and you're not entirely comfortable with tensor flow, then you can go with this pi torch thing. 

5. Open CV. 

Open CV is a very fancy most popular Python package that most developers love. So, it is a computer vision package, which can be used in all image processing tasks. So whether it is I mean self-driving car, or whether it is an object detection model or a face detection model, biometric everything. So everything that involves in computer vision application can be well treated with Open CV. So yeah, you can use Open CV to build all those models; you can make a face detection model from scratch. Using open CV, you can create an object detection classifier; you can use this, I mean open CV-Library in any advanced level to build all those image processing applications. 

6. Beautiful Soup

Beautiful Soup, often called BS four, is one of the best web scraping libraries that one can use, so you can scrape data from any website using this fancy library called Beautiful Soup. It is still one of the most popular libraries; I mean on the side of web scraping, and developers love this because it is easy to get data from any website using this BS for so it can also be used as a cloud, it can also be used as a crawler for most of the people. 

7. TK, enter

If you're fancy about building goI based applications in Python, then TK enter is the best choice to choose. Because TK enter allows you to build Python applications in my interfaces, you can use TK inter to construct any application. And you don't need a web server for that because you are just building a GI-based app. And yes, it is allowed by many of the people. 

8. Pillow. 

Pillow is somewhat similar to open CV, but it is used in various image processing applications. So wherever there is a requirement with image data, you can use the pillow to Amin to manipulate the sizes of the images and handle the image data set. And yeah, for other image-related tasks, you can use the pad for that. 

9. Matplotlib

Matplotlib is a famous data visualization package that one can use to get insights from the data. So you can use matplotlib a with combination to pandas or NumPy. So you can get a mean high-level understanding from that. So you can create pie charts, you can create graphs, you can, I mean, you can create graph charts, you can create different kinds of charts using matplotlib very quickly. 

10. Blob

Text Blob is one of the popular NLP libraries. So if you don't know what NLP stands for natural language processing, where you deal with natural language, Tex, Prague is one of the popular picks. And it is an excellent Python package. You can do any NLP task by using this. You can perform functions like stemming lemmatization. And you can use text blob in extracting sentiment analysis out of data. So yeah, this is one of the finest Python packages to go for when you're working on natural language processing. 

And yeah, these are all 10 top python libraries that every developer should have in their mind when building advanced Python applications. Thank you for reading this article.