PYTHON 3

In this activity, you will work with the feature extraction process from a publicly available dataset that contains news articles.

1.0 Introduction In this activity, you will work with the feature extraction process from a publicly available dataset that contains news articles. 2.0 Familiarize with the dataset Read the dataset description document and answer the following questions. This document is available at ml You can include your answers in a Jupyter Notebook (1) How many samples does the dataset consist? (2) How many different categories (topics) does the dataset provide? (3) Pick 4 of your most favorite categories and write them down in your notebook. 3.0 Import the data (1) Read Loading the 20 newsgroups dataset" from the following link: (2) Use fetch_20newsgroups function to import the dataset. Make sure to change the categories from the example to the ones you picked in question 2.3. (3) How many news articles did you import (the quantity of imported news articles depends on the categories of your choice)? (4) Read "Extracting features from text files" from the same link above. We will go through this together in class. 1.0 Introduction In this activity, you will work with the feature extraction process from a publicly available dataset that contains news articles. 2.0 Familiarize with the dataset Read the dataset description document and answer the following questions. This document is available at ml You can include your answers in a Jupyter Notebook (1) How many samples does the dataset consist? (2) How many different categories (topics) does the dataset provide? (3) Pick 4 of your most favorite categories and write them down in your notebook. 3.0 Import the data (1) Read Loading the 20 newsgroups dataset" from the following link: (2) Use fetch_20newsgroups function to import the dataset. Make sure to change the categories from the example to the ones you picked in question 2.3. (3) How many news articles did you import (the quantity of imported news articles depends on the categories of your choice)? (4) Read "Extracting features from text files" from the same link above. We will go through this together in class