courseraАнализ данных

Transfer Learning for NLP with TensorFlow Hub

Курс от Coursera

Средний≈ 2 чАнглийский

О курсе

This is a hands-on project on transfer learning for natural language processing with TensorFlow and TF Hub. By the time you complete this project, you will be able to use pre-trained NLP text embedding models from TensorFlow Hub, perform transfer learning to fine-tune models on real-world data, build and evaluate multiple models for text classification with TensorFlow, and visualize model performance metrics with Tensorboard. Prerequisites: In order to successfully complete this project, you should be competent in the Python programming language, be familiar with deep learning for Natural Language Processing (NLP), and have trained models with TensorFlow or and its Keras API. 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.

Навыки, которые вы освоите

Embeddings Transfer Learning Model Evaluation Natural Language Processing Software Visualization Model Training Keras (Neural Network Library)Deep Learning Tensorflow Classification Algorithms Machine Learning Fine-tuning

Программа курса

1 модулей · 4 учебных материалов

01Transfer Learning for NLP with TensorFlow Hub4 материалов

Transfer Learning for NLP with TensorFlow Hub

Project-based Course OverviewЧтение Transfer Learning for NLP with TensorFlow HubЛабораторная Graded Quiz: Test your Project UnderstandingЗадание

Учитесь у экспертов

Snehan Kekre

Machine Learning Instructor