Udemy

Platform

English

Language

Data Science

Category

Natural Language Processing (NLP) with Python and NLTK

Practical Approach : Collecting and Preprocessing text data, Data Visualization, Model Building and NLP Apps

3.95 (150 reviews)

Students

7 hours

Content

Jul 2019

Last Update
Regular Price


What you will learn

Concepts and practical applications of Natural Language Processing using Python and NLTK.


Description

Natural Language Processing (NLP) is a hot topic into the Machine Learning field. 

This course is focused in practical approach with many examples and developing functional applications.  This course starts explaining you, how to get the basic tools for coding and also making a review of the main machine learning concepts and algorithms. After that this course offers you a complete explanation of the main tools in NLP such as: Text Data Assemble, Text Data Preprocessing, Text Data Visualization, Model Building and finally developing NLP applications.

Hot topics on NLP that I will cover with practical applications on this course are:

- Regular expressions - Scrapping the web

- Textract library for extracting text content

- Sentence splitter and tokenization

- Stemming and Lemmatization

- Stop and rare word removal

- Part of Speech (POS) tagging

- Chunking

- N-grams

- Bag of Words: TfidfVectorizer

- Frequency Chart

- Co-occurence matrix

- Word cloud library

- Text similarity

- Text clustering

- Latent Semantic Analysis

- Topic Modeling

- Text Classification

- Sentiment Analysis

- Word2Vec library

- Recommender Systems: Collaborative Filtering

- Spam detector app

- Social Media Mining on Twitter

and much more!...

In this course you will find a concise review of the theory with graphical explanations and for coding it uses Python language and NLTK library. 

Finally this course offers you many datasets and other resources for your practice and study.


The student has the opportunity to get a feedback from the instructor through Q&A forums, by email: machine.learning.eirl@gmail.com or by Twitter: @AILearningCQ


Screenshots

Natural Language Processing (NLP) with Python and NLTK
Natural Language Processing (NLP) with Python and NLTK
Natural Language Processing (NLP) with Python and NLTK
Natural Language Processing (NLP) with Python and NLTK

Content

Environment Setup and Installation

Introduction to the course NLP with Python and NLTK

Before starting this course read this Guidelines

Resources

Environment Setup: Anaconda for Windows

VirtualBox and Ubuntu

Environment Setup: Anaconda for Linux

Codes in Python 3.6 and Installation Instructions

Machine Learning Review

Introduction

Scikit-Learn

Machine Learning concepts: Overfitting, Underfitting and Cross Validation

Classification model and evaluation: Confusion matrix and ROC curve

Logistic Regression

Support Vector Machines

Decision Trees and Random Forest

KNN algorithm

GridSearchCV

K-means Clustering

PCA

Collecting Text Data

Regular Expressions - part 1

Regular Expressions - part 2

NLTK Installation

Web Scraping

Extracting text content from different media with Textract

Text Data Preprocessing

Sentence splitter and Tokenization

Stemming and Lemmatization

Stop word removal

Part of Speech (POS) tagging

Chunking

N-grams

Bag of Words: CountVectorizer, TfidfVectorizer

Text Data Visualization

Frequency Chart

Co-Occurrence Matrix

Word Cloud

Model building

Text Similarity

Text Clustering

Latent Semantic Analysis

Topic Modelling

Text Classification

Sentiment Analysis

Word2Vec

Recommender Systems : Collaborative Filtering part 1

Recommender Systems : Collaborative Filtering part 2

NLP applications

Text Summarization app

Spam detector app

Word2Vec on Wikipedia

Recommender System with KNN

Social Media Mining on Twitter

The End Class


Reviews

Y
Yali18 August 2020

Great NLP, Python and NLTK introductory course. This course has lots of simple concept and insightful knowledge, and is easy to learn.

S
Samyak19 June 2020

This course gives all basic information about NLP. However, the course is really suitable for the beginners, who wants to take a step into world of NLP

A
Andres27 September 2019

Excellent course. Straight to the point, clear and very relevant topics. Best NLP course that I have taken yet.

R
Roberto6 June 2019

i took the time to analized the data and is really helpfull sorry most of the curse is an advertisement of the others curses

D
Debashis24 December 2018

Good course to set your feet in NLP. Really helped me a lot in creating business solutions for my clients. Thank you.

K
Kannan2 December 2018

In the beginning I thought the course was not helping me much, but later on I reviewed some of the key concepts again by watching a few videos repeatedly. I was able to understand the concepts better. I was able to identify some concepts for which I could find some useful applications. I feel the foundations of Word2Vec could have been better explained. Nevertheless what is shown here is quite useful.

G
Gaurav30 November 2018

Lot of concepts of libraries are not explained in Practical terms. Compare to other NLP course, this course is aligned in coverage of topics plus more examples covered but does not take to Expert zone where one can do exercises on advance NLP. For basic or beginner level this course is good!

N
Nichole5 October 2018

I need to work in Python 3 not Python 2. When I purchased the course I tried to make sure I was only getting python 3 but it seems that is not the case here. While the theory will still be useful the syntax and how to will be deprecated and not useful.

A
Ahmed30 March 2018

good course , but need some improvment in chunking and manual feature extraction usng chunking and building models from that features ... use python 3 and try to add sentiment analyzer using deeplearning .. you can improve it also by adding Aspect based seentiment anlaysis .. using chunking fetaure extraction then clustering ... best reagrds

P
Patrick19 March 2018

Great overview with many python code examples of using natural language process, especially NLTK. Very knowledgeable instructor.

J
Jilani_shakoor@yahoo.com25 February 2018

Really well organized. Wished the author had taken one example with a two or three large text documents, but still I think this is a great starting point to understand text mining

A
Alex27 January 2018

Overall, I found this course to be an essential supplemental resources for a NLP project I am working on. I tried different courses within the Udemy site and this one was by far the most complete and useful. I would only suggest to have the code in Python 3 or to make sure that the code is also compatible to non-linux environments, but this is a big issue since to learn DS one needs to get dirty with the code.

G
Goede20 January 2018

Good intro to setup the workspace. Refresher of the classification methods. Videos are of good length. Screen quality can be improved/hard to see/read the text sometimes. Overall great course. Good job!!!


1403374

Udemy ID

10/21/2017

Course created date

11/22/2019

Course Indexed date
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