Top 5 Python frameworks for Data Science important to study abroad?

Asked by Shivangi Sahu almost 2 years ago

Answers 1
ananya singh

ananya singh

Undergrad student

Python frameworks for data science, you can find easily. Mainly I read articles like top 10 or 20 Python frameworks for data science. The only thing that matters here is how good they are. Choosing a good framework is as important as choosing an elective in your master program. Because based on that, the further opportunities in data scone will impact.

I have personally used many Python frameworks so I know what I’m talking about. When you apply for a data science master program, the interviewer asks what Python framework you have used in your experience. I mean it's not necessarily the question but directly or indirectly you will be asked to explain some Python frameworks.

My personal recommendations are :

Tensorflow & Kiras. Tensorflow is basically a machine learning framework which is based on Python. From simple calculation to building complicated neural networks it can doall. You just need to try it once. If you don’t know this already, it is backed by Google itself and has been in the market since 2007. It became an open source platform in 2015 and 2017, Tensorflow released an add-on package by the name of Kiras. Kites offer upper-level APIs and building blocks for deep learning modules.

Numpy. Numby is a library that is a package built on the Python language. Numpy offers very efficient numerical operations. If you are looking for a Python framework that is good for performing various numerical calculations and manipulating matrices, Nympy is for you. Unlike other Python frameworks , Nympy has something different. You can either use Numpy on its own or it can be used with other frameworks like Tensorflow.

Pandas. Pandas provide a high-level data structure & analysis tools for Python. Pandas is quite famous because everything you work on related to your data, it happens in a Series (1D Array) or a DataFrame (2D Array). If you are a Python enthusiast, you know how facilitative it is. Pandas can be used to manipulate the data, visualize or to load CSV or excel files. Pandas is very useful if you want to make your work with DataFrame easy.

Matplotlib. When you work in machine learning, data visualization becomes very important, right? Because it is possible that the outlines or suspicious values can be missing. Matplotlib is not just a popular framework but also one of the most widely used Python graphic libraries. It is mainly used to visualize data. Data visualization is important in creating graphs. You also get different back-ends like Qt, WX for the visualization with Matplotlib.

Natural Language Toolkit. NLTK is yet another good Python framework that you can use. It is a collection of Python modules that can be used for processing natural languages, hence the name. NLTK includes part-of-speech tagging, named entity recognition, classification etc. You can also use it to process text to complete word meanings, sentences or even entire texts.

There you go. These are the top 5 Python frameworks I can think of. Now even if I say these are the absolute best ones, there's no clear answer. Your style may suit you a different one. Just keep an open mind and try the ones you like. If you need some more Python frameworks examples, let me know.



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