Text-analytics-Classification-of-the-given-Topics-and-to-identify-the-most-used-programming-languae.

Machine Learning, python

Text Analysis: Text analysis is a process which allows the machine to extract and classify the information of text such as tweets, emails etc. Text classification:Text classification is a smart classification of text into categories. And just makes the whole process super-fast and efficient.

In the above example, we read the "RequirementsData.csv" file and we want to print the most used programming language,most used Tools and most used algorithms based on the count of programming langauge, tools used and algorithms respectively.

Using "value_counts()" function we can get the count of programming laguage, tools and algorithms. The most used language is the one which has a maximum number of counts. Similarly,most used algorithm and tools are the one which has max count.

Text classification can be done by using the set of training data. The training data is used to make sure the machine recognizes patterns in the data, the cross-validation data is used to ensure better accuracy and efficiency of the algorithm used to train the machine, and the test data is used to see how well the machine can predict new answers based on its training.

How to Run the .ipynb file?

1.Open the terminal (Ctrl + Alt + T).

2.Navigate to the folder where your .ipynb file saved.

3.Type jupyter notebook

4.Open the file that you want to read.

5.To run the program line by line press shift+Enter.