Top 10 Python Libraries for Machine Learning

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With the increase in the markets for smart products, auto-pilot cars and other smart products, the ML industry is on a rise. Machine learning is also one of the most prominent tools of cost-cutting in almost every sector of industry nowadays. ML libraries are available in many programming languages, but python being the most user-friendly and easy to manage language, and having a large developer community, is best suited for machine learning purposes and that's why many ML libraries are being written in Python.
Top 10 Python Libraries for Machine Learning

Satish Mehta Web Development 202

1. TensorFlow :

2. Numpy:

3. Natural Language Toolkit (NLTK):

4.Pandas

5. Scikit-Learn:

6. Keras:

7. PyTorch:

8. MlPack:

9. OpenCV:

10. Matplotlib:

Conclusion:

With the increase in the markets for smart products, auto-pilot cars and other smart products, the ML industry is on a rise. Machine Learning is also one of the most prominent tools of cost-cutting in almost every sector of industry nowadays. ML libraries are available in many programming languages, but python being the most user-friendly and easy to manage language, and having a large developer community, is best suited for machine learning purposes and that's why many ML libraries are being written in Python . Also, the python works seamlessly with C and C++ and so, the already written libraries in C/C++ can be easily extended to Python. In this tutorial, we will be discussing the most useful and best machine-learning libraries in the Python programming language.Website: https://www.tensorflow.org/ GitHub Repository: https://github.com/tensorflow/tensorflowDeveloped By: Google Brain TeamPrimary Purpose: Deep Neural NetworksTensorFlow is a library developed by the Google Brain team for the primary purpose of Deep Learning and Neural Networks. It allows easy distribution of work onto multiple CPU cores or GPU cores, and can even distribute the work to multiple GPUs. TensorFlow uses Tensors for this purpose. Tensors can be defined as a container that can store N-dimensional data along with its linear operations. Although it is production-ready and does support reinforcement learning along with Neural networks, it is not commercially supported which means any bug or defect can be resolved only by community help.Website: https://numpy.org/Github Repository: https://github.com/numpy/numpy Developed By: Community Project (originally authored by Travis Oliphant)Primary purpose: General Purpose Array ProcessingCreated on the…
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