Fine Tune BERT for Text Classification with TensorFlow

Overview

Embark on a journey to master text classification with the cutting-edge Bidirectional Transformers for Language Understanding (BERT) leveraging TensorFlow's powerful capabilities. Dive into this comprehensive 2.5-hour guided project, designed to equip you with the skills to preprocess and tokenize data specifically for BERT classification.

Gain hands-on experience in constructing TensorFlow input pipelines utilizing the tf.data API, and advance your expertise by training and evaluating a finely tuned BERT model for text classification purposes with TensorFlow 2 and TensorFlow Hub.

Before embarking on this learning adventure, ensure you possess a competent level of proficiency in the Python programming language, a solid understanding of deep learning principles within Natural Language Processing (NLP), and previous experience in model training using TensorFlow or its Keras API. This course is optimized for learners located in the North America region, with efforts underway to extend this enriching learning experience to other regions soon.

Offered through Coursera, this project falls under several key educational categories, including Deep Learning Courses, TensorFlow Courses, Natural Language Processing (NLP) Courses, and BERT Courses, making it a perfect match for enthusiasts eager to delve into the realm of advanced NLP techniques.

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Taught by

Snehan Kekre

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Subjects