NLP Course for Beginner
NLP Course for Beginner, available at $34.99, has an average rating of 4, with 12 lectures, 5 quizzes, based on 502 reviews, and has 73959 subscribers.
You will learn about Overview of NLP Understand and use techniques from NLP Learn to work with Text Files with Python Use NLTK for Sentiment Analysis Write your own sentiment analysis code in Python Introduction to some key techniques from NLP Write your own spam detection code in Python This course is ideal for individuals who are Python developers interested in learning how to use Natural Language Processing. or All Computer Science Students or Newcomers to NLP It is particularly useful for Python developers interested in learning how to use Natural Language Processing. or All Computer Science Students or Newcomers to NLP.
Enroll now: NLP Course for Beginner
Summary
Title: NLP Course for Beginner
Price: $34.99
Average Rating: 4
Number of Lectures: 12
Number of Quizzes: 5
Number of Published Lectures: 12
Number of Published Quizzes: 5
Number of Curriculum Items: 17
Number of Published Curriculum Objects: 17
Original Price: ₹1,199
Quality Status: approved
Status: Live
What You Will Learn
- Overview of NLP
- Understand and use techniques from NLP
- Learn to work with Text Files with Python
- Use NLTK for Sentiment Analysis
- Write your own sentiment analysis code in Python
- Introduction to some key techniques from NLP
- Write your own spam detection code in Python
Who Should Attend
- Python developers interested in learning how to use Natural Language Processing.
- All Computer Science Students
- Newcomers to NLP
Target Audiences
- Python developers interested in learning how to use Natural Language Processing.
- All Computer Science Students
- Newcomers to NLP
Welcome to the best Natural Language Processing course on the Udemy! 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, 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, 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.
Course Curriculum
Chapter 1: Introduction
Lecture 1: Getting Started with NLP
Lecture 2: NLTK Setup and Overview
Chapter 2: Basics
Lecture 1: Reading in Text Data
Lecture 2: Exploring the Dataset
Lecture 3: Regular Expression
Chapter 3: Preprocessing
Lecture 1: Removing Punctuation
Lecture 2: Tokenizing in Text
Lecture 3: Removing stopwords
Lecture 4: Stemming
Lecture 5: Lemmatization
Chapter 4: Count Vectorization
Lecture 1: Count Vectorization in NLP
Chapter 5: Project
Lecture 1: Spam Detection Model in NLP
Instructors
-
Code Warriors
The best place to learn, code and conquer – Once you have it -
Mayank Bajaj
Founder at Code Warriors
Rating Distribution
- 1 stars: 23 votes
- 2 stars: 34 votes
- 3 stars: 128 votes
- 4 stars: 146 votes
- 5 stars: 171 votes
Frequently Asked Questions
How long do I have access to the course materials?
You can view and review the lecture materials indefinitely, like an on-demand channel.
Can I take my courses with me wherever I go?
Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!
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