Natural Language Processing (NLP) with BERT

Movies reviews Semantic analysis using BERT

4.19 (1503 reviews)
Udemy
platform
English
language
Data Science
category
Natural Language Processing (NLP) with BERT
25,346
students
1 hour
content
Jun 2024
last update
FREE
regular price

What you will learn

Natural Language Processing

How to implement the BERT model

Sentiment Analysis

How to code in Python with Google Colab

Why take this course?

🎬 Dive into Semantic Analysis with BERT! 🚀

Course Headline:

Movies Reviews Semantic Analysis using BERT

Are you ready to dive right into one of the most exciting developments in data science right now? Natural Language Processing (NLP) with BERT is not just another course; it's a journey into the world of cutting-edge AI! 🧠✨

Why Learn BERT for NLP? 🤔 BERT, developed by Google, is a revolutionary algorithm in NLP that has redefined how machines understand and respond to human language. With its impressive performance on a variety of NLP tasks, it's a technology you can't afford to ignore. 🌟

Course Description:

Natural Language Processing (NLP) is everywhere - in your search engines, virtual assistants, and even in the movie reviews you read before deciding which flick to watch! BERT has taken NLP to new heights, and our course will teach you how to leverage this powerful tool using a dataset from IMDb - one of the most popular and authoritative sources for movie information on the internet. 🎥

What You'll Learn:

  • Part 1: Data Preprocessing

    • Loading the IMDB dataset
    • Creating the training and test sets
  • Part 2: Building the BERT model (Learn how to implement BERT from scratch, including its architecture and components)

  • Part 3: Training and evaluating the BERT model

    • Getting the learner instance
    • Training and evaluating the BERT model using Google's Colab environment

Why Learn with Ktrain?

Ktrain is a low-code Python library that simplifies complex NLP tasks, allowing you to focus on understanding and applying NLP concepts rather than getting bogged down in code. Plus, with Google Colab, you can work on your projects from anywhere, without the need for powerful hardware or software installations. 📦

Your Instructor:

Hadelin de Ponteves is an AI expert who will guide you through the basic components of NLP, the implementation of BERT models, and the intricacies of sentiment analysis with ease and expertise. You'll gain hands-on experience in Python coding within Google Colab, a skill that will be invaluable for your data science career.

Course Highlights:

  • Practical Learning Experience: Apply what you learn in real-world scenarios.
  • Hands-On Approach: Get hands-on practice with actual datasets and tasks.
  • Cutting-Edge Techniques: Learn the latest in NLP with BERT, a state-of-the-art model.
  • No Cost to You: Enroll for FREE and start your data science journey today!

Ready to Get Started? 🧵

Enroll now and join the ranks of data scientists who are mastering NLP with BERT. This course is your ticket to understanding and implementing one of the most significant breakthroughs in AI. Click the ‘Enroll Now’ button, and let's embark on this exciting adventure together! 🚀💻

Don't wait any longer - the future of data science is calling, and BERT is leading the charge! Sign up today and transform your data science skills with NLP.

Our review

📝 Overview of the "NLP with BERT Model" Course

The "NLP with BERT Model" course by Hadelin de Ponteves has garnered a global rating of 4.31, with all recent reviews pointing towards a positive reception of this free offering on Udemy. The course provides an introduction to one of the most powerful NLP algorithms developed by Google, which is the BERT (Bidirectional Encoder Representations from Transformers) model.

Pros:

  • Comprehensive Introduction: The course effectively covers the basics of the BERT model and offers a practical implementation using the Ktrain library.
  • Free Access: Students can access this valuable content at no cost, making it an affordable option for those interested in NLP with BERT.
  • Visual Aids: Visualizations of data models and word tag clouds are mentioned as aspects that would enhance the learning experience.
  • Practical Focus: The course is praised for its practical approach, allowing students to follow along using Google Colab provided at the beginning.
  • Clear Instructions: Hadelin de Ponteves' teaching method is commended for providing clear and concise instructions.
  • Real-World Application: Some reviews suggest that the course gives a glimpse into real-world applications of BERT, which is a crucial aspect for practical learning.
  • Engaging Content: The course is described as engaging, particularly when it comes to presenting Python files from the ktrain package.
  • Opening Doors: For beginners and experienced learners alike, this course opens up a vast field of opportunities in machine learning.

Cons:

  • Technical Issues: Some users have reported issues with screen resolution and legibility, suggesting that the instructor's screen should be zoomed in for better readability.
  • Limited Time Constraints: There is a suggestion that additional time could have been allocated to cover more theory behind BERT and its applications.
  • Incomplete Content: A few reviews indicate that the course could be expanded to include more about model evaluation and real-world data prediction.
  • Assumed Prior Knowledge: Some users felt that the course assumed a certain level of coding proficiency, which might not be ideal for complete beginners.
  • Font Size Concern: A couple of reviews mentioned the font size being too small, especially on large monitors.
  • Document Legibility: The low resolution of videos makes it difficult to see what the instructor is reading off documents, suggesting that documents should be zoomed in for clarity.
  • Lack of Evaluation: There are concerns about the lack of evaluation methods shown with BERT, specifically the mention of a learning rate plot.

Additional Notes:

  • Accessibility: Despite some technical issues, the course is short and to the point, which is appreciated by many users.
  • Learning Resources: Some users suggest that additional resources or tests with real text data would enhance the learning experience.
  • Community Response: Hadelin de Ponteves and his teaching methods continue to receive praise from students who have taken this and other courses.

Overall, the course is a solid introduction to BERT for those with some coding background looking to delve into NLP with practical applications. It is recommended that future iterations of the course address the technical issues and expand on the theoretical aspects for a more comprehensive understanding.

Charts

Price

Natural Language Processing (NLP) with BERT - Price chart

Rating

Natural Language Processing (NLP) with BERT - Ratings chart

Enrollment distribution

Natural Language Processing (NLP) with BERT - Distribution chart
2968892
udemy ID
4/7/2020
course created date
4/9/2020
course indexed date
Angelcrc Seven
course submited by