?How do recurrent neural networks (RNNs) contribute to natural language processing tasks

Recurrent neural networks are well-suited for processing sequential data, making them ideal for tasks such as language modeling, text generation, and machine translation. RNNs maintain a memory of previous inputs, allowing them to capture contextual information crucial for understanding and generating natural language.

?What are the advantages of using transformer-based models like BERT in natural language processing

Transformer-based models, such as BERT (Bidirectional Encoder Representations from Transformers), have revolutionized NLP tasks by capturing bidirectional context effectively. They excel in tasks like sentiment analysis, question answering, and text classification, outperforming traditional models by leveraging large-scale pretraining on vast amounts of text data.

Deep Learning in Natural Language Processing Tutorial

How to Get The Certificate

You must have an account Register
Watch All Lessons
Watch at least 50% of Lesson Duration
you can follow your course progress From Your Profile
You can Register With Any Course For Free
The Certificate is free !

Lessons | 3

00:14:17

What is Hadoop and Parallel Processing Hadoop Tutorial for Beginners Big Data Great Learning

00:31:56

Deep Learning in Natural Language Processing Analytics Masterclass Tutorial Great Learning

00:53:44

Asia s First Agriculture Information System Webinar Agrisk Data Analytics Great Learning

We Appreciate Your Feedback

Excellent		2 Reviews
Good		2 Reviews
medium		0 Reviews
Acceptable		0 Reviews
Not Good		0 Reviews

4.5

4 Reviews

How Much Stars ?

What is Your Feedback ?

Dhrsaj Kaushal

Good course. 2024-11-08

Sourish Chakraborty

good course 2024-04-14

Bhargav Mandava

Good 2024-04-13

Gupta sourab

Good course 2024-04-05

Show More Reviews

Our New Certified Courses Will Reach You in Our Telegram Channel
Join Our Telegram Channels to Get Best Free Courses

Join Now

Related Courses

7 Lessons

Natural Language Understanding

Deep Learning in Natural Language course in hindi, in this course we will learn about the application of deep learning techniques in natural language processing tasks. Explore neural network architectures such as recurrent neural networks (RNNs) and transformers. Dive into sentiment analysis, named entity recognition, machine translation, and other NLP tasks using state-of-the-art deep learning models. Gain practical skills in text processing, feature engineering, and model evaluation to tackle real-world NLP challenges effectively.

Deep Learning in Natural Language Processing

Computer Science

How to Get The Certificate

What is Hadoop and Parallel Processing Hadoop Tutorial for Beginners Big Data Great Learning

Deep Learning in Natural Language Processing Analytics Masterclass Tutorial Great Learning

Asia s First Agriculture Information System Webinar Agrisk Data Analytics Great Learning

Linear Algebra for Computer Scientists

Insertion Sort

Bubble Sort

GCSE Computer Science

Random Access Memory

Binary Trees

Bitwise Operators

Introduction to Stacks Data Structures

Organization Theory Structure and Design

Handling Large Scale Unit Level Data Using STATA

Introduction to Machine Learning

Applied Linear Algebra Vectors Matrices and Least Squares

Artificial Intelligence Principles and Techniques

Machine Learning Autumn 2018

Robotics and Autonomous Systems

Natural Language Understanding