Python is a highly demanding language, and its soaring popularity has made it even more desirable in the programming world.  Speaking of the numbers, there are ideally 8.2 million Python users, according to SlashData. Adding up, if you expect to become a data scientist, Python unfurls more opportunities in your career. If you are looking to start a career in IT, choose Srishti Campus for the best Python training centre in Trivandrum, Kerala. 

To bolster your career as a data scientist, here are the top five Python libraries you need to check! 

TensorFlow: Specifically used for high performance, TensorFlow facilitates numerical computations with nearly 35,000 comments. It also has an excellent and responsive community with more than 1000+ contributors. It is a framework used solely for designing, running, and computing involving tensors.  TensorFlow is ideally the perfect fit for applications requiring speech and image recognition, time-series analysis, and video detection. 

NumPy: A powerful N-dimensional array object is included in NumPy, the Python library for numerical computation. GitHub has around 18,000 comments and 700 active contributors. It provides high-performance multidimensional objects called arrays as well as tools for working with them. As well as providing multidimensional arrays, NumPy also provides functions and operators that operate efficiently on these arrays. 

Matplotlib: With extremely interesting and intense visualisations, Matplotlib has a plotting library for Python consisting of around 26,000 comments on GitHub. Along with that, it also has a vibrant community of around 700 contributors. It is extensively used for data visualisation due to the graphs and plots it produces. Furthermore, it provides an object-oriented API for embedding those plots into applications. 

SciPy: Scientific Python or SciPy is yet another free and open source of Python Library exclusive for data scientists and science. It is solely used for high-level computations. On GitHub, SciPy has around 19,000 comments and about 600 contributors. As it extends NumPy, it is exclusively used for scientific and technical calculations. 

Keras: Keras is yet another famous library used a lot for deep learning and neural network modules. It supports and assists TensorFlow and Theano at the backends, making it the best choice if one wants to use something other than the former. The library also provides an elaborate prelabeled dataset which can be used to directly import and load. 

These libraries not only strengthen the Python framework’s use and applications but also help you to become well-versed in this much demanded software language. To know and learn more about Python language, enroll to one of the best software training institutes in India and unfurl different scopes of learning Python language.