Introduction to Spacy 3 for Natural Language Processing

Kick start your Data Science career with NLP. This course is about Spacy. NLTK is not taught in this course.

4.30 (128 reviews)
Udemy
platform
English
language
Data Science
category
instructor
Introduction to Spacy 3 for Natural Language Processing
4,934
students
4 hours
content
Jul 2022
last update
$19.99
regular price

What you will learn

Complete Spacy Lesson

Introduction to NLP

Tokenization in Spacy

NER and Dependency Parsing

Regular Expression

Emoji Detection for Sentiment Analysis

Description

Hi There,

Please take this course only if you have an introductory knowledge of Machine Learning and Python.


This course is all about SpaCy. Spacy is fast and easy to use than NLTK. It is one of the fundamental building blocks of today's modern NLP. SpaCy is an open-source software library for advanced natural language processing, written in the programming languages Python and Cython. The library is published under the MIT license and its main developers are Matthew Honnibal and Ines Montani, the founders of the software company Explosion.


Get things done

SpaCy is designed to help you do real work — to build real products or gather real insights. The library respects your time and tries to avoid wasting it. It's easy to install, and its API is simple and productive. We like to think of spaCy as the Ruby on Rails of Natural Language Processing.


Blazing fast

SpaCy excels at large-scale information extraction tasks. It's written from the ground up in carefully memory-managed Cython. Independent research in 2015 found spaCy to be the fastest in the world. If your application needs to process entire web dumps, spaCy is the library you want to be using.


Deep learning

spaCy is the best way to prepare the text for deep learning. It interoperates seamlessly with TensorFlow, PyTorch, scikit-learn, Gensim, and the rest of Python's awesome AI ecosystem. With spaCy, you can easily construct linguistically sophisticated statistical models for a variety of NLP problems.


Features

  • Non-destructive tokenization

  • Named entity recognition

  • Support for 59+ languages

  • 46 statistical models for 16 languages

  • Pretrained word vectors

  • State-of-the-art speed

  • Easy deep learning integration

  • Part-of-speech tagging

  • Labeled dependency parsing

  • Syntax-driven sentence segmentation

  • Built-in visualizers for syntax and NER

  • Convenient string-to-hash mapping

  • Export to NumPy data arrays

  • Efficient binary serialization

  • Easy model packaging and deployment

  • Robust, rigorously evaluated accuracy

  • And so much more.


Content

Introduction

Introduction to NLP
Install Spacy
Introduction to Spacy
Tokenization
Parts of Speech [POS] Tagging
Dependency Visualization
Named Entity Recognition (NER)
Sentence Segmentation
Rule Based Phrase Matching
Regular Expression Part 1
Regular Expression Part 2
Processing Pipeline in Spacy
Hashtags and Emoji Detection

Reviews

Alokkumar
August 13, 2021
Awesome Explanation. This Course assists aspiring data scientists to specialize in natural language processing
Florian
June 8, 2021
I was a vey nice Introduction course, some parts were confusing. For example Matcher.add() method got updated by SpaCy and in this course the old version is handled. But thats not anyones fault. What i would recommend sometimes is maybe a more clear english. All in all very nice, thanks to Mr. Kant
Marcio
January 15, 2021
Curso muito bom. Didática muito boa. Simples e prático. Muito bom para manipular um pequeno texto, mas não serve para os meus propósitos: de um longo texto, a partir de palavras chaves que antecedem o trecho que me interessa, extrair as linhas imediatamente posteriores, até a ocorrência de outra palavra chave. Mas eu recomendo para conhecer o funcionamento da biblioteca/pacote.
Sachin
December 13, 2020
I really like the instructor's explanation and its easy and crisp to grasp. I really thanks to KGP team to create such kind of course which is missing in Udemy.
Sushant
December 7, 2020
The course content is rich with a good explanation, exercises. I love the instructor how he taught. KCP Talkie courses are excellent and preferred for both beginners and developers. Thanks for this freat free course.
Guillermo
August 25, 2020
Although quite small and short, pretty concise and clear to understand. Really looking forward the more advanced stuf
Noman
August 23, 2020
It's good enough as an introduction course! But not that easy for python beginners.. But overall, thanks for creating such a useful course. I like it!
Sriram
August 18, 2020
Nice Tutorial. I have been following KGP Talkie in Youtube too for a long time and those tutorials helped me a lot. Laxmikanth has good knowledge on all Data Science areas - be it Pandas or Data Viz or NLP or TensorFlow - and this is pretty much evident from his bag of work. Recommended!
Arald
August 2, 2020
This is the best introduction to Spacy that I have seen. The material is clear. There is a lot of very practical examples.I would had more Spacy Regex examples and talk about high performance throughput. Since that is the main reason to use Spacy or else one can just use NLTK.
Anuj
July 21, 2020
Worth of investing in it. Awesome intro. You need to have ML knowledge before starting this course. Thanks Laxmi Kant.

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Coupons

DateDiscountStatus
6/18/2022100% OFF
expired
3306778
udemy ID
7/6/2020
course created date
7/10/2020
course indexed date
Angelcrc Seven
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