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NLP – Natural Language Processing With Python

What you’ll be taught

  • Study to work with Textual content Information with Python
  • Learn to work with PDF information in Python
  • Make the most of Common Expressions for sample looking in textual content
  • Use Spacy for extremely quick tokenization
  • Find out about Stemming and Lemmatization
  • Perceive Vocabulary Matching with Spacy
  • Use A part of Speech Tagging to mechanically course of uncooked textual content information
  • Perceive Named Entity Recognition
  • Visualize POS and NER with Spacy
  • Use SciKit-Study for Textual content Classification
  • Use Latent Dirichlet Allocation for Subject Modelling
  • Find out about Non-negative Matrix Factorization
  • Use the Word2Vec algorithm
  • Use NLTK for Sentiment Evaluation
  • Use Deep Studying to construct out your personal chat bot
Necessities
  • Perceive normal Python
  • Have permissions to put in python packages onto laptop
  • Web connection

Description

Welcome to the most effective Pure Language Processing course on the web! This course is designed to be your full on-line useful resource for studying tips on how to use Pure Language Processing with the Python programming language.

Within the course we are going to cowl every little thing it’s worthwhile to be taught in an effort to change into a world class practitioner of NLP with Python.

We’ll begin off with the fundamentals, studying tips on how to open and work with textual content and PDF information with Python, in addition to studying tips on how to use common expressions to seek for customized patterns inside textual content information.

Afterwards we are going to start with the fundamentals of Pure Language Processing, using the Pure Language Toolkit library for Python, in addition to the state-of-the-art Spacy library for extremely quick tokenization, parsing, entity recognition, and lemmatization of textual content.

We’ll perceive basic NLP ideas resembling stemming, lemmatization, cease phrases, phrase matching, tokenization and extra!

Subsequent we are going to cowl Half-of-Speech tagging, the place your Python scripts will have the ability to mechanically assign phrases in textual content to their applicable a part of speech, resembling nouns, verbs and adjectives, an important a part of constructing clever language programs.

We’ll additionally study named entity recognition, permitting your code to mechanically perceive ideas like cash, time, corporations, merchandise, and extra just by supplying the textual content data.

By means of state-of-the-art visualization libraries we might be ready view these relationships in actual time.

Then we are going to transfer on to understanding machine studying with Scikit-Study to conduct textual content classification, resembling mechanically constructing machine studying programs that may decide constructive versus damaging film critiques, or spam versus reputable e mail messages.

We are going to increase this information to extra advanced unsupervised studying strategies for pure language processing, resembling matter modelling, the place our machine studying fashions will detect subjects and main ideas from uncooked textual content information.

This course even covers superior subjects, resembling sentiment evaluation of textual content with the NLTK library, and creating semantic phrase vectors with the Word2Vec algorithm.

Included on this course is a whole part dedicated to state-of-the-art superior subjects, resembling utilizing deep studying to construct out our personal chat bots!

Not solely do you get improbable technical content material with this course, however additionally, you will get entry to each our course associated Query and Reply boards, in addition to our reside scholar chat channel, so you possibly can workforce up with different college students for tasks, or get assistance on the course content material from myself and the course educating assistants.

All of this comes with a 30 day a refund garuantee, so you possibly can attempt the course danger free.

What are you ready for? Develop into an knowledgeable in pure language processing at this time!

I’ll see you contained in the course,

Who this course is for:

  • Python builders occupied with studying tips on how to use Pure Language Processing.

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