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Popular Python Libraries For Data Science And Best Tutorials To Learn Them

Python libraries  for data science

Summary: Pandas is one of the best tool for data wrangling or munging. It is built for quick & easy data manipulation, reading, aggregation, data viz,  etc.

1. Pandas

Summary: NumPy (Numerical Python) is a perfect tool for scientific computing and performing basic and advanced array operations.

2. numpy

Summary: TensorFlow can be used across a range of tasks but has a particular focus on training and inference of deep neural networks. 

3. TensorFlow

Summary: Using this library, you can determine percentage accuracy, compute loss function, create custom function layers, built-in data and image processing, etc.

4. keras

Summary: Scikit-learn is used for for handling standard machine learning and data mining tasks such as clustering, dimensionality reduction, and classification.

5. Scikit-learn

Summary: This library is one of the most popular, fast, open-source web crawling frameworks written in Python. 

6. Scrapy

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Check Out Best Free Resources To Learn Top Python Data Science Libraries From The Below-Given Link