INFINITE SKILLS NATURAL LANGUAGE TEXT PROCESSING WITH PYTHON-iLLiTERATE
General:Training

Size: 465.88 MB

## Jonathan Mugan
## Estimated time to complete: 1h 52m
## Topics Natural Language Processing
## Published byInfinite Skills 2017

>> 2018x12
>> 10x50
>> +1

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Even though computers can't read, they're very effective
at extracting information from natural language text
They can determine the main themes in the text, figure
out if the writers of the text have positive or negative
feelings about what they've written, decide if two
documents are similar, add labels to documents, and
more

This course shows you how to accomplish some common NLP
(natural language processing) tasks using Python, an
easy to understand, general programming language, in
conjunction with the Python NLP libraries, NLTK, spaCy
gensim, and scikit-learn. The course is designed for
basic level programmers with or without Python
experience

Gain practical hands-on natural language processing
experience using Python
Understand how to tokenize text so it can be
processed as symbols
Learn to convert text and words to vectors using
TF-IDF and word2vec
Explore dependency parsing, sentiment analysis, and
LDA topic modeling

an external knowledge base
Understand the capabilities and limitations of
natural language text processing

Jonathan Mugan is CEO and co-founder of DeepGrammar, a
natural language processing company. Jonathan has a PhD
in computer science from the University of Texas, and
has been working in AI and machine learning since 2003
He describes his research focus as "making the squishy
reality of our everyday world available to computation."

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