Learn BERT - essential NLP algorithm by Google from Udemy

Master BERT: The Breakthrough NLP Algorithm

Course Overview:

Welcome to the ultimate guide to BERT. This comprehensive course is designed to take you on a journey from the basics to mastery of BERT (Bidirectional Encoder Representations from Transformers), a state-of-the-art algorithm transforming the field of natural language processing (NLP).

Why Choose This Course?

Accessible for Everyone: Whether you're a seasoned data scientist or a newcomer to NLP, this course is crafted to be inclusive and comprehensive. We begin with the origins and history of BERT, carefully explaining each concept so that anyone can follow along. By the end of the course, you'll have a solid grasp of BERT, regardless of your starting point.

Revolutionary and Versatile: BERT has fundamentally changed how we approach NLP tasks by eliminating the need for traditional models like RNNs and CNNs. Instead, BERT uses transformers to provide a more intuitive and effective way to process language. You'll learn how to apply BERT to a wide range of NLP tasks, making your projects more powerful and efficient.

Practical: We prioritize practicality and usability in this course. Using TensorFlow 2.0 and Google Colab, you'll avoid common issues with local machine setups and software compatibility. These tools ensure that you are learning with the most current and advanced technologies available. You'll gain hands-on experience with real-world applications, reinforcing your learning and giving you the confidence to apply BERT in your own projects.

Hands-On Learning: Our course includes numerous practical exercises and projects to help you apply what you’ve learned. You'll work through real-world scenarios and datasets, allowing you to see firsthand how BERT can be used to solve complex NLP problems. This hands-on approach ensures that you're not just learning theory but also gaining the practical skills needed to implement BERT effectively.

Enroll Now:

If you're ready to dive into the world of BERT and revolutionize your approach to natural language processing, this course is for you. Enroll now and start your journey towards mastering one of the most powerful tools in NLP today.

What's inside

Learning objectives

Understand the history about bert and why it changed nlp more than any algorithm in the recent years
Understand how bert is different from other standard algorithm and is closer to how humans process languages
Use the tokenizing tools provided with bert to preprocess text data efficiently
Use the bert layer as a embedding to plug it to your own nlp model
Use bert as a pre-trained model and then fine tune it to get the most out of it
Explore the github project from the google research team to get the tools we need
Get models available on tensorflow hub, the platform where you can get already trained models

Clean text data
Create datasets for ai from those data
Use google colab and tensorflow 2.0 for your ai implementations
Create customs layers and models in tf 2.0 for specific nlp tasks
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Understand the history about bert and why it changed nlp more than any algorithm in the recent years
Understand how bert is different from other standard algorithm and is closer to how humans process languages
Use the tokenizing tools provided with bert to preprocess text data efficiently
Use the bert layer as a embedding to plug it to your own nlp model
Use bert as a pre-trained model and then fine tune it to get the most out of it
Explore the github project from the google research team to get the tools we need
Get models available on tensorflow hub, the platform where you can get already trained models
Clean text data
Create datasets for ai from those data
Use google colab and tensorflow 2.0 for your ai implementations
Create customs layers and models in tf 2.0 for specific nlp tasks
Show more
Show less

Syllabus

Introduction

Welcome to the course

Course curriculum, Colab toolkit and data links

EXTRA: Learning Path

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Taught by Martin Jocqueviel, SuperDataScience Team, and Ligency Team, who are recognized for their work in NLP

Examines BERT, which is highly relevant to NLP

Develops NLP skills that are core to NLP

Teaches how to use BERT as a pre-trained model, building a strong foundation for beginners in NLP

This hands-on training with real-world applications strengthens an existing foundation for intermediate learners in NLP

This course uses Google Colab and Tensorflow 2.0 for AI implementations, which may require learners to come in with extensive background knowledge

Reviews summary

Practical bert for nlp professionals

According to students, this course offers a highly practical and comprehensive guide to BERT, especially benefiting those with some NLP or deep learning background. Learners praise its clear explanations of complex concepts like transformers, making BERT accessible. The emphasis on hands-on coding with TensorFlow 2.0 and Google Colab stands out, leading to seamless implementation and immediate application. While past reviews noted initial dependency issues, recent feedback confirms the course is actively updated and improved. However, some learners desired deeper dives into code or more advanced topics.

Course content is kept current with necessary software updates.

"The corrections mentioned in the syllabus seem to have addressed earlier issues, as I didn't face major dependency problems."

"The support for new package versions was a huge plus."

"I see now there are 'corrections' in the syllabus, so hopefully, that has improved, but my initial experience was quite negative."

Effectively demystifies complex BERT and NLP theories.

"The explanations on transformers and attention mechanisms were incredibly clear, demystifying complex concepts."

"The instructor broke down difficult concepts into understandable segments."

"The clarity in explaining complex topics like tokenization and fine-tuning was exceptional."

Focuses heavily on hands-on exercises and real-world implementation.

"I particularly appreciated the hands-on labs with TensorFlow 2.0 and Google Colab; it made applying the knowledge straightforward and immediately useful."

"It explains BERT's architecture and pre-training thoroughly, then quickly moves into practical applications."

"The course includes numerous practical exercises and projects to help you apply what you’ve learned."

Some learners desired more detailed explanations of coding choices.

"I found some of the code explanations a bit brief, and occasionally the transition between theoretical concepts and code implementation felt abrupt."

"I managed to get through it, but it required extra research."

"The coding parts sometimes felt like 'run this code' without enough explanation of *why* certain choices were made."

Best suited for learners with some prior deep learning or NLP knowledge.

"I think the course assumes a basic familiarity with deep learning concepts, so true beginners might find some parts challenging."

"Perhaps it's for those already very familiar with advanced NLP and TensorFlow, not for someone trying to learn BERT from scratch."

"My only minor feedback is that some advanced optimization techniques or edge cases could have been explored a bit more."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Learn BERT - essential NLP algorithm by Google with these activities:

Learn About BERT Basics

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Start the course off strong with a firm grasp on the basics of what BERT is and how it's used.

Browse courses on Natural Language Processing

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Watch Introduction to BERT video on course landing page.
Review course notes on BERT history and architecture.
Complete the BERT Intuition quiz.

BERT Tokenization Exercise

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Reinforce your understanding of how BERT tokenizes text data by completing this exercise.

Browse courses on Natural Language Processing

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Load the necessary libraries and import the text data.
Create a BERT tokenizer using the appropriate function.
Tokenize the text data using the BERT tokenizer.
Print the tokenized text data to verify the results.

BERT As An Embedder Demo

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Solidify your knowledge of using BERT as an embedder by creating a demo that showcases its capabilities.

Browse courses on Natural Language Processing

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Load the necessary libraries and import the required data.
Create a BERT model and load the pre-trained weights.
Use the BERT model to generate embeddings for the input text.
Visualize the embeddings using a dimensionality reduction technique.

Two other activities

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BERT Resource Collection

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Facilitate future learning by compiling a collection of valuable BERT resources, tools, and tutorials.

Browse courses on Natural Language Processing

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Search for and identify relevant BERT resources.
Organize the resources into a structured format.
Document the resources and provide brief descriptions.

Fine-Tuning BERT for Question Answering

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Challenge yourself by fine-tuning a pre-trained BERT model for question answering tasks, deepening your understanding of its capabilities.

Browse courses on Question Answering

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Load the necessary libraries and import the required data.
Load a pre-trained BERT model and fine-tune it for question answering.
Train the model on the question answering dataset.
Evaluate the model's performance on a held-out dataset.

Career center

Learners who complete Learn BERT - essential NLP algorithm by Google will develop knowledge and skills that may be useful to these careers:

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Learn BERT - essential NLP algorithm by Google

What's inside

Learning objectives

Syllabus

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Reviews summary

Practical bert for nlp professionals

Activities

Career center

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