Transfer Learning for NLP with TensorFlow Hub

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4.5

(4)

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Course Features

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Duration

1.5 hour

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Delivery Method

Online

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Available on

Limited Access

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Accessibility

Desktop, Laptop

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Language

English

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Level

Intermediate

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Teaching Type

Self Paced

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Video Content

1.5 hour

Course Description

This project focuses on transfer learning for natural-language processing using TensorFlow or TF Hub. You will be able use TensorFlow Hub pre-trained NLP text embedding model, perform transfer learning to fine tune models on real-world data and build multiple models for text classification using TensorFlow. Tensorboard can also visualize model performance metrics. You must be proficient in Python programming and familiar with deep learning for Natural Language Processing (NLP). This course is best for those who live in North America. The same experience is being offered in other areas.

Course Overview

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Virtual Labs

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International Faculty

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Case Based Learning

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Post Course Interactions

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Case Studies,Instructor-Moderated Discussions

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Case Studies, Captstone Projects

Skills You Will Gain

What You Will Learn

Use pre-trained NLP text embedding models from

Perform transfer learning to fine-tune models on real-world text data

Visualize model performance metrics with

Showcase this hands-on experience in an interview

Course Instructors

Snehan Kekre

Machine Learning Instructor

Snehan Kekre is a Documentation Writer at Streamlit, the fastest and easiest way to build and share data apps. He has authored and taught over 40+ guided projects on machine learning and data science...

Course Reviews

Average Rating Based on 4 reviews

4.5

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25%

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