Why Python is a Boon for Programmers
What is common between companies like Quora, YouTube, Google, and Journyx? All of these companies are data driven, they rely a lot on the use of Machine Learning and, most importantly, all of these companies use Python extensively.
People often ask this question – “I am a programmer and want to get into data science. What should I do? Should I learn R? Should I learn Python?” In this post, I will try to answer these questions.
If you are a programmer and are trying to get into data science, learning Python will be a good decision.
2. Python has very good machine learning libraries: The variety of machine learning libraries that are available in Python is large. One can choose between Scikitlearn, Keras, Theano and Tensorflow. Many neural network libraries such as Keras, Theano etc., are exclusively available in Python. So, if you want to do cutting edge machine learning work, you must know Python.
3. Python excels at handling text data: Unlike statistical software environments such as R, Python excels at handling text data. People who know Python can easily mine text corpus for useful insights. Python also provides support for Natural Language Processing through NLTK and sPacy
4. Python makes distributed computing very easy: Apache Spark has a Python API called PySpark. Using this piece of software, one can easily do distributed computing. PySpark has in recent times become the de-facto API for Spark.
5. Extensive support for different data sources: It doesn’t matter if one needs to fetch data from an SQL server, a MongoDB database or JSON data from some web API; Python can easily support all these data sources with a very clean and elegant syntax.
Learning Python has many advantages – it gives a user many skills, one can fetch data from different sources, create machine learning models and do distributed computing seamlessly. For any programmer, learning Python will not be a difficult task. One can reap a lot of benefits by devoting time to learning Python.
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