Udemy
    •  
    •  
    •  
    •  
    •  
    •  
    •  
    •  
Turn what you know into an opportunity and reach millions around the world.
Learn More
Your cart is empty.
Keep shopping
Deep learning: A Natural Language Processing Bootcamp
Rating: 4.1 out of 5(17 ratings)
3,963 students

Deep learning: A Natural Language Processing Bootcamp

Learn NLP the RIGHT WAY!
Created byAditya Shankarnarayan
Last updated 1/2022
English
English [Auto],

What you'll learn

  • Natural Language Processing
  • Deep Learning
  • Machine Learning
  • Sentiment Analysis
  • Tensorflow
  • Neural Networks

Course content

2 sections • 25 lectures • 1h 16m total length

  • Welcome0:55
  • Introduction1:38
  • Neural Network2:24

    Explore the structure of neural networks, including input and hidden layers, weights, biases, and activation functions like relu and sigmoid, plus basics of learning, classification, and regularization to prevent overfitting.

  • Google Colab1:36
  • Tokenization3:48
  • Coding: Tokenization2:32

    Explore how tokenization works in natural language processing by examining how punctuation is handled, how words are indexed by frequency, and how a vocabulary is built without separate punctuation tokens.

  • Vocabulary3:48
  • OOV2:40
  • Coding: OOV2:30
  • Padding1:50
  • Coding: Padding6:15

    Explore padding in text sequences for deep learning, including tokenization, vocabulary, and max length. Compare front and back zero padding and see how fixed-length inputs affect model training.

  • Sarcasm Dataset3:02
  • Coding: Sarcasm Dataset5:24

    Adding flatten wont crash colab, might not work in this instance but surely can be used.

  • Class Project1:10
  • Wrap up!1:23

Requirements

  • Basics of Python 3 programming

Description

Master Natural Language Processing with TensorFlow – From Basics to Building Real Projects

Unlock the power of Natural Language Processing (NLP) using TensorFlow in this hands-on, beginner-friendly course. Whether you're just curious about NLP or looking to build real-world applications, this course is designed to guide you step-by-step through both theory and implementation.


What You’ll Learn:

  • Tokenization – Break down text into meaningful components (Part 1)

  • Word Embeddings – Learn how to represent words as vectors (Part 2)

This course emphasizes hands-on learning. You’ll implement every concept as you go—because real understanding comes from building, not just watching.

And for those who love the "why" behind the "how", we dive deep into the theory too. You'll explore state-of-the-art NLP techniques, including tokenization, embeddings, RNNs, and more—with clear explanations and practical examples.


Who This Course Is For:

  • Curious learners ready to explore NLP

  • Aspiring developers who want to build text-based applications

  • Anyone eager to understand and implement NLP with TensorFlow

Prerequisites:

  • Basic arithmetic skills

  • A solid foundation in Python programming

  • Familiarity with basic TensorFlow operations

“If you can’t implement it, you don’t understand it.”


Join me in this exciting journey through NLP, where you’ll not only learn the concepts but also create real-world solutions with them.

Who this course is for:

  • Beginner python developer curious about Data Science
  • Data Scientists
  • Developers

Report abuse