Python is unquestionably the most trending computer language in the world right now. As we are observing the trajectory, its demand skyrocketed in the last 5 years, and experts believe it will continue to go up. Now, the question is what makes Python so popular in the first place. Here we will discuss the top 10 most popular python libraries.
There are several reasons which make Python incredible. It is easy to learn, relevant to future needs, and, of course, most users believe it is ideal for AI-based projects. However, we will cover a different aspect of its popularity – its vast library.
Top 10 Most Popular Python Libraries
In this section, we will talk about the 10 most popular Python libraries that you should be aware of as we are moving along in 2021.
TensorFlow is one of the most popular Python libraries in the world, especially for those who are into machine learning projects.
Developed by a company called Brain Team in alliance with Google, TensorFlow can write new algorithms which give a great deal of creativity to the users. It is flexible and you can train the CPU and GPU with ease. Since the library is Open-Source, you can customize it as you like.
If you are looking for a library that can help you binding some complex data, we suggest you use Scikit-Learn. It comes with some robust features like cross-validation, feature extraction, and many more.
Alongside that, you can also take help from the training methods. The likes of logistics regression and nearest neighbors are two notable features. Another reason that may compel you to use Scikit-Learn is its various algorithms. Some notable traits include clustering, factor analysis, principal component analysis, and a lot more.
Numpy is more like a dedicated Python library for machine learning projects. Other libraries like TensorFlow and Scikit-Learn also uses Numpy to get what they want. First and foremost, it is very easy to use. Probably that is the reason people love to use it. You can do difficult maths at jet-speed.
One other reason most people like it is because you can do coding with ease as its concepts are mostly understandable. Numpy is an open-source app that is intuitive and interactive at the same time.
Next on our list is Keras, which is also very efficient in AI-based projects. You can express neural networks without breaking a sweat here, and with the help of its incredible features, you can get a project done much faster.
You can run Keras in both CPU and GPU efficiently, and due to its flexible nature, you can tweak exactly as the project demands. In short, Keras is portable and effective and should get your attention.
PyTorch is yet another efficient Python library that has tremendous potentiality. It comes with a Hybrid Front-end that you can use to elements both in the eager and the graph mode, all maintaining a C++ environment.
Apart from that, you can take advantage of the distribution training for P2P communications, which you can check from both Python and C++. Overall, you should check out PyTorch as it also comes with various tools.
LightGBM is a part of Gradient Boosting, which many experts believe one of the best Python libraries in the world right now. The reason so many Python developers admire this library is because of its fast computation trait.
That ensures you can do your job efficiently at a faster pace. Also, it is user-friendly, stated by most users who use it. When compared to most libraries, you can train on LightGBR at a significantly faster rate.
The crucial factor is while you are considering NaN values, it emits fewer errors compared to others.
When you are predominantly looking for a Python library to sort out various mathematical equations, we believe you should give Eli5 a try. It can work in collaboration with XGBoost, lightning, Scikit-learn, and many more.
So, you might have guessed already that this library is flexible and you can tweak it about it effortlessly. On top of that, you can add legacy applications and try out new skills in various areas. So, we believe you should check on it once.
Also Read: Top 5 Online Courses for Python Programming
If you are an application developer or an engineer whose main focus area is machine learning, you should definitely check out SciPy. You can do linear algebras, integrations, statistical analysis, and many more pivotal tasks with SciPy. One of the most crucial factors is it can work with NumPy the best.
Both the libraries complement each other, and therefore, you can do a lot using them. The reason for SciPy to be famous is mainly because it is well-documented. Therefore, it is easy to learn and use. So, you too should give it a shot.
Theano is ideal if you are into computing multidimensional arrays. You can work with Theano, which most people would agree works similar to TensorFlow.
One of its useful traits is, of course, working with NumPy, and the way you can perform data-intensive computations, make it perfect use in the GPUs. Also, you can use Dynamic C code generation with ease. So, Theano worth your time.
Pandas is one of the most-used Python libraries for data structures of high-level. There are loads of inbuilt methods that you can use to customize your project to its maximum efficiencies.
The likes of grouping, combining data, and filtering are some noteworthy examples. So, you should also give Pandas a pass while you need to elevate your project.
We agree there are loads of Python libraries that you can also check on. However, we have gathered a list that is first of all, popular, and second of all has a distinct quality that will elevate your project to another level.