Advance Your Skills in Natural Language Processing
Offered By: LinkedIn Learning
Course Description
Overview
Natural language processing is quickly emerging as a key skill for machine learning engineers. This advanced-level learning path provides machine learning engineers with advanced NLP techniques and tools to further their knowledge in this industry-defining field.
- Translate text data into powerful insights using Python.
- Learn about transformers, the go-to architecture of NLP.
- Build NLP apps with transformers.
Syllabus
Courses under this program:
Course 1: Advanced NLP with Python for Machine Learning (2020)
-Build upon your foundational knowledge of natural language processing (NLP) by exploring more complex topics such as word2vec, doc2vec, and recurrent neural networks.
Course 2: Hands-On Natural Language Processing
-Learn to use natural language processing to make sense of text data and derive useful insights.
Course 3: Building NLP Pipelines with spaCy
-Learn the essentials of problem-solving with spaCy, the popular, open-source software library for advanced natural language processing.
Course 4: Deep Learning Foundations: Natural Language Processing with TensorFlow
-Learn foundational deep learning techniques to classify, predict, and generate text using different neural networks.
Course 5: Recurrent Neural Networks
-Learn the basics of recurrent neural networks to get up and running with RNN quickly.
Course 6: Generative AI: Working with Large Language Models
-Explore a user-friendly approach to working with transformers and large language models for natural language processing.
Course 1: Advanced NLP with Python for Machine Learning (2020)
-Build upon your foundational knowledge of natural language processing (NLP) by exploring more complex topics such as word2vec, doc2vec, and recurrent neural networks.
Course 2: Hands-On Natural Language Processing
-Learn to use natural language processing to make sense of text data and derive useful insights.
Course 3: Building NLP Pipelines with spaCy
-Learn the essentials of problem-solving with spaCy, the popular, open-source software library for advanced natural language processing.
Course 4: Deep Learning Foundations: Natural Language Processing with TensorFlow
-Learn foundational deep learning techniques to classify, predict, and generate text using different neural networks.
Course 5: Recurrent Neural Networks
-Learn the basics of recurrent neural networks to get up and running with RNN quickly.
Course 6: Generative AI: Working with Large Language Models
-Explore a user-friendly approach to working with transformers and large language models for natural language processing.
Courses
-
Build upon your foundational knowledge of natural language processing (NLP) by exploring more complex topics such as word2vec, doc2vec, and recurrent neural networks.
-
Learn the basics of recurrent neural networks to get up and running with RNN quickly.
-
Learn to use natural language processing to make sense of text data and derive useful insights.
-
Explore a user-friendly approach to working with transformers and large language models for natural language processing.
-
Learn foundational deep learning techniques to classify, predict, and generate text using different neural networks.
-
Learn the essentials of problem-solving with spaCy, the popular, open-source software library for advanced natural language processing.
Taught by
Derek Jedamski, Wuraola Oyewusi, Prateek Sawhney, Harshit Tyagi, Kumaran Ponnambalam and Jonathan A. Fernandes
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