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NLTK and
NetworkX
Installing NLTK and networkX
pip3 install nltk
pip3 install networkx
if you want to download specific NLTK module ,class or resources:
• Go to terminal
• Type python3
• Type import nltk
• Type nltk.download(‘stopwords’) //to download ‘stopwords’ resource
• Type nltk.download('punkt') // includes data and models used for sentence
tokenization.
NLTK
• NLTK stands for "Natural Language Toolkit." It is a Python
library and platform designed to help with language data (text)
for various natural language processing (NLP) tasks.
• Provides a suite of classes are designed to facilitate the
implementation of different NLP algorithms.
• Tokenization
• Stemming and Lemmatization
• Part-of-Speech Tagging
• Corpus and Text Collections and many more
CORPORA in NLTK
• In NLTK ,"corpora" refers to collections of text that are used for
training, testing, and experimenting with (NLP) techniques and
algorithms.
• Some example of corpora:
1.Brown Corpus: A collection of text from various genres, representing
different writing styles and topics. It's often used for studying linguistic
patterns and trends.
2.Inaugural Address Corpus: Includes the inaugural speeches of U.S.
presidents, which can be analyzed for linguistic and historical trends.
Importing a Specific Corpora
import nltk
nltk.download(‘corpora_name')
from nltk.corpus import ‘corpora_name’
Eg - from nltk.corpus import inaugural
Importing other classes from different nltk modules
from nltk.probability import FreqDist
• used to compute the frequency distribution of items in a given sequence, such as a list of
words.
• helpful tool for analyzing the frequency of words in a text corpus.
STOPWORDS
• In NLTK, "stopwords" refer to common words that are often removed
from text when performing natural language processing tasks like text
analysis, sentiment analysis, and information retrieval.
• Have no or little significant meaning
• Examples are "and" "the," "is," "in," "of," etc.
Sample code for Stopwords
Stemming
• a text normalization technique used in natural language processing to reduce
words to their base or root form.
• simplify words so that variations of the same word (e.g., "running," "runs,"
"ran") are treated as the same word.
• NLTK (Natural Language Toolkit) library provides various stemmers :
• Porter Stemmer
• Lancaster Stemmer
• Snowball Stemmer
Counter
• Counter is a class from the collections module that is used to count the
occurrences of elements in a collection.
DefaultDict
• The defaultdict class is also provided by the collections module.
• allows you to create dictionaries with a default value for keys that do
not exist.
• Also allows you to create a custom default function
NETWORKX
• NetworkX is a Python library used for the
creation, manipulation, and analysis of graphs.
• provides tools for working with a variety of
network structures, such as directed and
undirected graphs, multigraphs, and more.
• Can also add edge attributes as optional
arguments.
MST Using NetworkX

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Assignment4.pptx

  • 2. Installing NLTK and networkX pip3 install nltk pip3 install networkx if you want to download specific NLTK module ,class or resources: • Go to terminal • Type python3 • Type import nltk • Type nltk.download(‘stopwords’) //to download ‘stopwords’ resource • Type nltk.download('punkt') // includes data and models used for sentence tokenization.
  • 3. NLTK • NLTK stands for "Natural Language Toolkit." It is a Python library and platform designed to help with language data (text) for various natural language processing (NLP) tasks. • Provides a suite of classes are designed to facilitate the implementation of different NLP algorithms. • Tokenization • Stemming and Lemmatization • Part-of-Speech Tagging • Corpus and Text Collections and many more
  • 4. CORPORA in NLTK • In NLTK ,"corpora" refers to collections of text that are used for training, testing, and experimenting with (NLP) techniques and algorithms. • Some example of corpora: 1.Brown Corpus: A collection of text from various genres, representing different writing styles and topics. It's often used for studying linguistic patterns and trends. 2.Inaugural Address Corpus: Includes the inaugural speeches of U.S. presidents, which can be analyzed for linguistic and historical trends.
  • 5. Importing a Specific Corpora import nltk nltk.download(‘corpora_name') from nltk.corpus import ‘corpora_name’ Eg - from nltk.corpus import inaugural Importing other classes from different nltk modules from nltk.probability import FreqDist • used to compute the frequency distribution of items in a given sequence, such as a list of words. • helpful tool for analyzing the frequency of words in a text corpus.
  • 6. STOPWORDS • In NLTK, "stopwords" refer to common words that are often removed from text when performing natural language processing tasks like text analysis, sentiment analysis, and information retrieval. • Have no or little significant meaning • Examples are "and" "the," "is," "in," "of," etc.
  • 7. Sample code for Stopwords
  • 8. Stemming • a text normalization technique used in natural language processing to reduce words to their base or root form. • simplify words so that variations of the same word (e.g., "running," "runs," "ran") are treated as the same word. • NLTK (Natural Language Toolkit) library provides various stemmers : • Porter Stemmer • Lancaster Stemmer • Snowball Stemmer
  • 9.
  • 10. Counter • Counter is a class from the collections module that is used to count the occurrences of elements in a collection.
  • 11. DefaultDict • The defaultdict class is also provided by the collections module. • allows you to create dictionaries with a default value for keys that do not exist. • Also allows you to create a custom default function
  • 12. NETWORKX • NetworkX is a Python library used for the creation, manipulation, and analysis of graphs. • provides tools for working with a variety of network structures, such as directed and undirected graphs, multigraphs, and more. • Can also add edge attributes as optional arguments.