Introduction to NLP

Introduction to NLP, available at Free, has an average rating of 3.5, with 10 lectures, based on 133 reviews, and has 3355 subscribers.

You will learn about Basics of Natural Language Processing This course is ideal for individuals who are Beginner NLP It is particularly useful for Beginner NLP.

Enroll now: Introduction to NLP

Summary

Title: Introduction to NLP

Price: Free

Average Rating: 3.5

Number of Lectures: 10

Number of Published Lectures: 10

Number of Curriculum Items: 10

Number of Published Curriculum Objects: 10

Original Price: Free

Quality Status: approved

Status: Live

What You Will Learn

Basics of Natural Language Processing

Who Should Attend

Beginner NLP

Target Audiences

Beginner NLP

Natural Language processing is today a fast-emerging technology area. It has also been one of the most difficult topics to handle for the computers. Thanks to the advancement in artificial intelligence, we can process natural language more easily today. Many business applications today leverage the power of NLP. With the perfection on speech to text and text to speech conversions, NLP tools are used today as personal assistants and robo advisors. The chat bots are primary interface for many business applications. The NLP engine can process vast amounts of texts and classify them as well as translate them to another language. NLP programs are working in conjunction with the image recognition techniques to automatically generate captions from the images and the vice-versa.

This course is tries to demystify some aspects of NLP and address some of the challenges and approaches to handle the same.

Expectations from the course

1. Why NLP is important

2. Complexity in handling NLP

3. Business use cases of NLP

4. Different types of NLP problems

5. Approach for solving NLP problems

6. Applying machine learning concepts

7. Word embedding

This course uses python programming for basic hands-on. Some of the practice sessions in this course include: –

1. Standard text handling using nltk

2. Pre-processing text (normalization)

3. Sentiment analysis of the review comments

4. Spam detection using machine learning algorithms

Course Curriculum

Chapter 1: Background and concepts

Lecture 1: Introduction to the course

Lecture 2: NLP concepts

Chapter 2: NLP approaches

Lecture 1: NLP Approaches

Chapter 3: Preprocessing of texts

Lecture 1: Concepts – Text normalization

Lecture 2: Preprocessing of Texts

Chapter 4: Rule based approaches for NLP

Lecture 1: Concepts – Rules based approaches

Lecture 2: Practice session – Sentiment Analysis

Chapter 5: Probabilistic models for NLP

Lecture 1: Probabilistic models

Lecture 2: Practice Session – Spam classification

Chapter 6: NLP using Deep Learning

Lecture 1: NLP using Deep Learning

Instructors

Sunil Mishra
Instructor at Udemy

Rating Distribution

1 stars: 3 votes
2 stars: 6 votes
3 stars: 23 votes
4 stars: 39 votes
5 stars: 62 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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