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Feature Engineering for NLP in Python

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4+
13 reviews
Updated 12/2024
Learn techniques to extract useful information from text and process them into a format suitable for machine learning.
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PythonMachine Learning4 hours15 videos52 exercises4,200 XP25,228Statement of Accomplishment

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Course Description

In this course, you will learn techniques that will allow you to extract useful information from text and process them into a format suitable for applying ML models. More specifically, you will learn about POS tagging, named entity recognition, readability scores, the n-gram and tf-idf models, and how to implement them using scikit-learn and spaCy. You will also learn to compute how similar two documents are to each other. In the process, you will predict the sentiment of movie reviews and build movie and Ted Talk recommenders. Following the course, you will be able to engineer critical features out of any text and solve some of the most challenging problems in data science!

Prerequisites

Introduction to Natural Language Processing in PythonSupervised Learning with scikit-learn
1

Basic features and readability scores

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2

Text preprocessing, POS tagging and NER

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3

N-Gram models

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4

TF-IDF and similarity scores

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Feature Engineering for NLP in Python
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*4
from 13 reviews
54%
23%
8%
0%
15%
  • Gildas T.
    7 days

    Great course, learned a lot. I can already apply my knowledge to get insights from textual data, and not only that, but also understand and predict sentiments. Fantastic. However, whilst the teaching content are great, some code blocks or line needs to be updated. Thank you for the course!

  • Hamed H.
    8 months

    The course is really Straight forward and it contains many tasks to do which is really nice

  • Ankush B.
    9 months

    Excellent course for learning concepts related to feature engineering in NLP and their application in Python.

  • Cherlynn A.
    about 1 year

    Thank you. It was incredible.

  • Pierre-Etienne T.
    over 1 year

    Synthetic, exciting and relevant

"Great course, learned a lot. I can already apply my knowledge to get insights from textual data, and not only that, but also understand and predict sentiments. Fantastic. However, whilst the teaching content are great, some code blocks or line needs to be updated. Thank you for the course!"

Gildas T.

"The course is really Straight forward and it contains many tasks to do which is really nice"

Hamed H.

"Excellent course for learning concepts related to feature engineering in NLP and their application in Python."

Ankush B.

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