Preprocess and clean data for BERT Classification
Load in pretrained BERT with custom output layer
Train and evaluate finetuned BERT architecture on your own problem statement
In this 2-hour long project, you will learn how to analyze a dataset for sentiment analysis. You will learn how to read in a PyTorch BERT model, and adjust the architecture for multi-class classification. You will learn how to adjust an optimizer and scheduler for ideal training and performance. In fine-tuning this model, you will learn how to design a train and evaluate loop to monitor model performance as it trains, including saving and loading models. Finally, you will build a Sentiment Analysis model that leverages BERT's large-scale language knowledge. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.
In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:
Introduction to BERT and the problem at hand
Exploratory Data Analysis and Preprocessing
Loading Tokenizer and Encoding our Data
Setting up BERT Pretrained Model
Creating Data Loaders
Setting Up Optimizer and Scheduler
Defining our Performance Metrics
Creating our Training Loop
Loading and Evaluating our Model
Your workspace is a cloud desktop right in your browser, no download required
In a split-screen video, your instructor guides you step-by-step
Clean, clear and helpful. Thanks a lot! Would also be nice to see the approaches to tune BERT for the particular task (e.g. custom tokenization, pre-processing of data, etc.)
Thanks to Mr.Ari Anastassiou Sentiment Analysis with Deep Learning using BERT! is been really a wonderful project .Enjoyed it
There could have been more explanation about the libraries and the module 6,7,8 and 9 could have covered more deeply.
The instructor explains very well on how to using bert to train a sentiment classifier. Very cool project.
What will I get if I purchase a Guided Project?
By purchasing a Guided Project, you'll get everything you need to complete the Guided Project including access to a cloud desktop workspace through your web browser that contains the files and software you need to get started, plus step-by-step video instruction from a subject matter expert.
Are Guided Projects available on desktop and mobile?
Because your workspace contains a cloud desktop that is sized for a laptop or desktop computer, Guided Projects are not available on your mobile device.
Who are the instructors for Guided Projects?
Guided Project instructors are subject matter experts who have experience in the skill, tool or domain of their project and are passionate about sharing their knowledge to impact millions of learners around the world.
Can I download the work from my Guided Project after I complete it?
You can download and keep any of your created files from the Guided Project. To do so, you can use the “File Browser” feature while you are accessing your cloud desktop.
What is the refund policy?
Is financial aid available?
Financial aid is not available for Guided Projects.
Can I audit a Guided Project and watch the video portion for free?
Auditing is not available for Guided Projects.
How much experience do I need to do this Guided Project?
At the top of the page, you can press on the experience level for this Guided Project to view any knowledge prerequisites. For every level of Guided Project, your instructor will walk you through step-by-step.
Can I complete this Guided Project right through my web browser, instead of installing special software?
Yes, everything you need to complete your Guided Project will be available in a cloud desktop that is available in your browser.
What is the learning experience like with Guided Projects?
You'll learn by doing through completing tasks in a split-screen environment directly in your browser. On the left side of the screen, you'll complete the task in your workspace. On the right side of the screen, you'll watch an instructor walk you through the project, step-by-step.
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