NLP - Natural Language Processing with Python from Udemy

Welcome to the best Natural Language Processing course on the internet. This course is designed to be your complete online resource for learning how to use Natural Language Processing with the Python programming language.

In the course we will cover everything you need to learn in order to become a world class practitioner of NLP with Python.

We'll start off with the basics, learning how to open and work with text and PDF files with Python, as well as learning how to use regular expressions to search for custom patterns inside of text files.

Afterwards we will begin with the basics of Natural Language Processing, utilizing the Natural Language Toolkit library for Python, as well as the state of the art Spacy library for ultra fast tokenization, parsing, entity recognition, and lemmatization of text.

We'll understand fundamental NLP concepts such as stemming, lemmatization, stop words, phrase matching, tokenization and more.

Next we will cover Part-of-Speech tagging, where your Python scripts will be able to automatically assign words in text to their appropriate part of speech, such as nouns, verbs and adjectives, an essential part of building intelligent language systems.

We'll also learn about named entity recognition, allowing your code to automatically understand concepts like money, time, companies, products, and more simply by supplying the text information.

Through state of the art visualization libraries we will be able view these relationships in real time.

Then we will move on to understanding machine learning with Scikit-Learn to conduct text classification, such as automatically building machine learning systems that can determine positive versus negative movie reviews, or spam versus legitimate email messages.

We will expand this knowledge to more complex unsupervised learning methods for natural language processing, such as topic modelling, where our machine learning models will detect topics and major concepts from raw text files.

This course even covers advanced topics, such as sentiment analysis of text with the NLTK library, and creating semantic word vectors with the Word2Vec algorithm.

Included in this course is an entire section devoted to state of the art advanced topics, such as using deep learning to build out our own chat bots.

Not only do you get fantastic technical content with this course, but you will also get access to both our course related Question and Answer forums, as well as our live student chat channel, so you can team up with other students for projects, or get help on the course content from myself and the course teaching assistants.

All of this comes with a 30 day money back garuantee, so you can try the course risk free.

What are you waiting for? Become an expert in natural language processing today.

I will see you inside the course,

Jose

What's inside

Learning objectives

Learn to work with text files with python
Learn how to work with pdf files in python
Utilize regular expressions for pattern searching in text
Use spacy for ultra fast tokenization
Learn about stemming and lemmatization
Understand vocabulary matching with spacy
Use part of speech tagging to automatically process raw text files
Understand named entity recognition
Visualize pos and ner with spacy

Use scikit-learn for text classification
Use latent dirichlet allocation for topic modelling
Learn about non-negative matrix factorization
Use the word2vec algorithm
Use nltk for sentiment analysis
Use deep learning to build out your own chat bot
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Learn to work with text files with python
Learn how to work with pdf files in python
Utilize regular expressions for pattern searching in text
Use spacy for ultra fast tokenization
Learn about stemming and lemmatization
Understand vocabulary matching with spacy
Use part of speech tagging to automatically process raw text files
Understand named entity recognition
Visualize pos and ner with spacy
Use scikit-learn for text classification
Use latent dirichlet allocation for topic modelling
Learn about non-negative matrix factorization
Use the word2vec algorithm
Use nltk for sentiment analysis
Use deep learning to build out your own chat bot
Show more
Show less

Syllabus

Introduction

Course Overview - DO NOT SKIP THIS LECTURE PLEASE. IMPORTANT INFO HERE!

Please make sure to watch the Course Overview Lecture.

Thanks!

Curriculum Overview

Installation and Setup Lecture

FAQ - Frequently Asked Questions

Let's learn how to work with basic .txt and .pdf files.

Introduction to Python Text Basics

Working with Text Files with Python - Part One

Working with Text Files with Python - Part Two

Working with PDFs

Regular Expressions Part One

Regular Expressions Part Two

Python Text Basics - Assessment Overview

Python Text Basics - Assessment Solutions

Let's learn the basics of NLP, NLTK, and Spacy with Python!

Introduction to Natural Language Processing

Spacy Setup and Overview

What is Natural Language Processing?

Spacy Basics

Tokenization - Part One

Tokenization - Part Two

Stemming

Lemmatization

Stop Words

Phrase Matching and Vocabulary - Part One

Phrase Matching and Vocabulary - Part Two

NLP Basics Assessment Overview

NLP Basics Assessment Solution

Let's learn about Part of Speech Tagging and Named Entity Recognition with Python and NLP!

Introduction to Section on POS and NER

Part of Speech Tagging

Visualizing Part of Speech

Named Entity Recognition - Part One

Named Entity Recognition - Part Two

Visualizing Named Entity Recognition

Sentence Segmentation

Part Of Speech Assessment

Part Of Speech Assessment - Solutions

Let's learn how to utilize Scikit-Learn and Machine Learning to conduct Text Classification

Introduction to Text Classification

Machine Learning Overview

Classification Metrics

Confusion Matrix

Scikit-Learn Primer - How to Use SciKit-Learn

Scikit-Learn Primer - Code Along Part One

Scikit-Learn Primer - Code Along Part Two

Text Feature Extraction Overview

Text Feature Extraction - Code Along Implementations

Text Feature Extraction - Code Along - Part Two

Text Classification Code Along Project

Text Classification Assessment Overview

Text Classification Assessment Solutions

Learn how to create semantic word vectors and conduct sentiment analysis!

Introduction to Semantics and Sentiment Analysis

Overview of Semantics and Word Vectors

Semantics and Word Vectors with Spacy

Sentiment Analysis Overview

Sentiment Analysis with NLTK

Sentiment Analysis Code Along Movie Review Project

Sentiment Analysis Project Assessment

Sentiment Analysis Project Assessment - Solutions

Let's learn unsupervised learning techniques such as Latent Dirichlet Allocation and Non-negative Matrix Factorization

Introduction to Topic Modeling Section

Overview of Topic Modeling

Latent Dirichlet Allocation Overview

Latent Dirichlet Allocation with Python - Part One

Latent Dirichlet Allocation with Python - Part Two

Non-negative Matrix Factorization Overview

Non-negative Matrix Factorization with Python

Topic Modeling Project - Overview

Topic Modeling Project - Solutions

Let's now dive into deep learning to conduct text generation and build chat bots!

Introduction to Deep Learning for NLP

The Basic Perceptron Model

Introduction to Neural Networks

Keras Basics - Part One

Keras Basics - Part Two

Recurrent Neural Network Overview

LSTMs, GRU, and Text Generation

Text Generation with LSTMs with Keras and Python - Part One

Text Generation with LSTMs with Keras and Python - Part Two

Text Generation with LSTMS with Keras - Part Three

Chat Bots Overview

Creating Chat Bots with Python - Part One

Creating Chat Bots with Python - Part Two

Creating Chat Bots with Python - Part Three

Creating Chat Bots with Python - Part Four

THANK YOU!

BONUS LECTURE

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Provides a comprehensive foundation in Natural Language Processing using Python, suitable for beginners with no prior NLP experience

Covers both fundamental NLP concepts and advanced topics like sentiment analysis and chat bot building

Utilizes industry-standard libraries like NLTK and Spacy, equipping learners with practical skills for real-world NLP applications

Includes hands-on projects and assessments throughout the course, reinforcing learning and providing opportunities for practical application

Led by Jose Portilla, an experienced instructor with a strong reputation in NLP education

Offers a 30-day money-back guarantee, providing learners with peace of mind and flexibility

Reviews summary

Positive nlp journey

Learners say this course has high quality lectures that provide the background knowledge and Python code necessary to understand NLP. Students conclude that topics are well-defined and that this course is outstanding.

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in NLP - Natural Language Processing with Python with these activities:

SQL Primer

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Refamiliarize yourself with the basics of SQL to set yourself up for success in working with complex datasets

Browse courses on SQL

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Review basic SQL syntax, including SELECT, INSERT, UPDATE, DELETE, and CREATE statements
Practice writing queries to retrieve data from a database
Create a simple database schema and populate it with data
Challenge yourself with more complex queries, such as those involving joins and subqueries

Natural Language Processing with Python: Analyzing Text with the Natural Language Toolkit

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Gain a solid foundation in NLP concepts and techniques by reading this comprehensive book

View Natural Language Processing with Python:... on Amazon

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Read the chapters on tokenization, stemming, and lemmatization
Understand the principles of part-of-speech tagging and named entity recognition
Explore the use of NLTK for various NLP tasks
Work through the exercises and examples provided in the book

NLP Blog or Article

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Share your knowledge and understanding of NLP by writing a blog post or article

Browse courses on Natural Language Processing

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Choose a specific NLP topic that you are knowledgeable about
Research and gather information from credible sources
Write a well-structured and informative article that is easy to understand
Proofread and edit your article carefully before publishing it

Two other activities

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Natural Language Processing in Python

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Expand your knowledge of NLP techniques and their applications by following guided tutorials

Browse courses on Natural Language Processing

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Explore tutorials on tokenization, stemming, and lemmatization
Experiment with part-of-speech tagging and named entity recognition
Gain experience in text classification and sentiment analysis
Learn how to use libraries such as NLTK and spaCy for NLP tasks
Build a small NLP project, such as a spam filter or a text summarizer

NLP Coding Challenges

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Sharpen your NLP coding skills by solving practice problems and challenges

Browse courses on Natural Language Processing

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Participate in online coding competitions and hackathons focused on NLP
Contribute to open-source NLP projects and collaborate with other developers
Solve NLP puzzles and brain teasers to enhance your problem-solving abilities
Create your own NLP coding challenges and share them with others

Career center

Learners who complete NLP - Natural Language Processing with Python will develop knowledge and skills that may be useful to these careers:

Natural Language Processing Specialist

This course is designed for people who want to work in the field of natural language processing (NLP). NLP is a subfield of artificial intelligence that deals with the interaction between computers and human (natural) languages. As a Natural Language Processing Specialist, you will use your knowledge of NLP to develop and improve computer systems that can understand and generate human language. This course will provide you with the skills you need to work as a Natural Language Processing Specialist, including how to use Python to develop NLP applications.

See salaries and explore the career path for Natural Language Processing Specialist

Computational Linguist

Computational Linguistics is a field that combines computer science and linguistics to develop computational models of human language. As a Computational Linguist, you will use your knowledge of linguistics and computer science to develop and improve computer systems that can understand and generate human language. This course will provide you with the skills you need to work as a Computational Linguist, including how to use Python to develop NLP applications.

See salaries and explore the career path for Computational Linguist

Machine Learning Engineer

Machine Learning Engineers develop and deploy machine learning models to solve real-world problems. Natural language processing is a subfield of machine learning, so this course can be helpful for people who want to work as Machine Learning Engineers. This course will provide you with a foundation in NLP that you can use to develop and deploy machine learning models for NLP tasks.

See salaries and explore the career path for Machine Learning Engineer

Data Scientist

Data Scientists use data to solve real-world problems. Natural language processing is a subfield of data science, so this course can be useful for people who want to work as Data Scientists. This course will provide you with a foundation in NLP that you can use to develop and deploy NLP models for data science tasks.

See salaries and explore the career path for Data Scientist

Software Engineer

Software Engineers develop and maintain software applications. Natural language processing is a subfield of software engineering, so this course can be helpful for people who want to work as Software Engineers. This course will provide you with a foundation in NLP that you can use to develop and deploy NLP applications.

See salaries and explore the career path for Software Engineer

Information Architect

Information Architects design and organize websites and other information systems. Natural language processing is a subfield of information architecture, so this course can be helpful for people who want to work as Information Architects. This course will provide you with a foundation in NLP that you can use to design and organize information systems that are easy for people to use.

See salaries and explore the career path for Information Architect

User Experience Designer

User Experience Designers design and evaluate the user experience of websites and other products. Natural language processing is a subfield of user experience design, so this course can be helpful for people who want to work as User Experience Designers. This course will provide you with a foundation in NLP that you can use to design and evaluate user experiences for NLP applications.

See salaries and explore the career path for User Experience Designer

Content Writer

Content Writers create written content for websites, blogs, and other platforms. Natural language processing is a subfield of content writing, so this course can be helpful for people who want to work as Content Writers. This course will provide you with a foundation in NLP that you can use to create written content that is clear, concise, and engaging.

See salaries and explore the career path for Content Writer

Editor

Editors review and edit written content for accuracy, clarity, and consistency. Natural language processing is a subfield of editing, so this course can be helpful for people who want to work as Editors. This course will provide you with a foundation in NLP that you can use to review and edit written content for accuracy, clarity, and consistency.

See salaries and explore the career path for Editor

Technical Writer

Technical Writers create written content that explains technical concepts to non-technical audiences. Natural language processing is a subfield of technical writing, so this course can be helpful for people who want to work as Technical Writers. This course will provide you with a foundation in NLP that you can use to create written content that is clear, concise, and engaging.

See salaries and explore the career path for Technical Writer

Librarian

Librarians help people find and access information. Natural language processing is a subfield of library science, so this course can be helpful for people who want to work as Librarians. This course will provide you with a foundation in NLP that you can use to help people find and access information more effectively.

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Archivist

Archivists preserve and provide access to historical records. Natural language processing is a subfield of archival science, so this course can be helpful for people who want to work as Archivists. This course will provide you with a foundation in NLP that you can use to preserve and provide access to historical records more effectively.

See salaries and explore the career path for Archivist

Museum curator

Museum Curators oversee the care and display of museum collections. Natural language processing is a subfield of museum studies, so this course can be helpful for people who want to work as Museum Curators. This course will provide you with a foundation in NLP that you can use to oversee the care and display of museum collections more effectively.

See salaries and explore the career path for Museum curator

Historian

Historians study the past. Natural language processing is a subfield of history, so this course can be helpful for people who want to work as Historians. This course will provide you with a foundation in NLP that you can use to study the past more effectively.

See salaries and explore the career path for Historian

Archaeologist

Archaeologists study human history through the excavation and analysis of material remains. Natural language processing is a subfield of archaeology, so this course can be helpful for people who want to work as Archaeologists. This course will provide you with a foundation in NLP that you can use to study human history through the excavation and analysis of material remains more effectively.

See salaries and explore the career path for Archaeologist