Natural Language Processing with Sequence Models
This course is part of Natural Language Processing.
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Natural Language Processing Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
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vپښتو, বাংলা, اردو, 4 more
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What you'll learn
Train neural networks for sentiment analysis using GLoVe embeddings
Generate synthetic text using Gated Recurrent Units (GRU)
Implement named entity recognition using LSTM networks
Develop Siamese networks for question similarity analysis
Build practical NLP applications with deep learning
Skills you'll gain
This course includes:
1.7 Hours PreRecorded video
3 quizzes
Access on Mobile, Tablet, Desktop
FullTime access
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There are 3 modules in this course
This course focuses on advanced natural language processing techniques using sequence models. Students learn to implement sentiment analysis using neural networks with GLoVe word embeddings, generate synthetic text using GRUs, perform named entity recognition with LSTMs, and develop Siamese networks for identifying similar questions. The course combines theoretical understanding with practical implementation through hands-on programming assignments and real-world applications.
Recurrent Neural Networks for Language Modeling
Module 1 · 10 Hours to complete
LSTMs and Named Entity Recognition
Module 2 · 4 Hours to complete
Siamese Networks
Module 3 · 6 Hours to complete
Fee Structure
Individual course purchase is not available - to enroll in this course with a certificate, you need to purchase the complete Professional Certificate Course. For enrollment and detailed fee structure, visit the following: Natural Language Processing
Instructors
Stanford AI Educator Pioneers Global Learning Through Course Innovation and EdTech Leadership
Younes Bensouda Mourri is a distinguished AI educator and entrepreneur who has significantly impacted global tech education. Born and raised in Morocco, he earned his B.S. in Applied Mathematics and Computer Science and M.S. in Statistics from Stanford University, where he now teaches Artificial Intelligence both on campus and online. As the founder of LiveTech.AI, he develops AI tools to transform academic institutions, while his courses have reached over 1.3 million learners worldwide, with 23% securing AI-related jobs after completion. His contributions include co-creating Stanford's Applied Machine Learning, Deep Learning, and Teaching AI courses, as well as developing the highly successful Natural Language Processing Specialization for DeepLearning.AI. Starting as a teaching assistant in Andrew Ng's Machine Learning course, he rose to become an Adjunct Lecturer at Stanford by age 22, demonstrating his commitment to democratizing AI education. Through his work with major companies like ASML, CISCO, and Boston Consulting Group, he continues to advance AI education while focusing on developing innovative NLP tools for personalized feedback and chain-of-thought reasoning
Pioneering AI Education and Product Management
Eddy Shyu is a prominent AI Product Manager at Cisco, with a notable background in curriculum development as the former Curriculum Product Manager at DeepLearning.AI. He has played a crucial role in creating approximately 40 online courses focused on artificial intelligence, which have reached over 2 million learners across platforms such as Coursera, DeepLearning.AI, Udacity, and Cisco Networking Academy. Eddy's expertise extends to designing educational content that simplifies complex AI concepts for diverse audiences, ensuring accessibility and engagement in learning. His work includes leading the creation of Andrew Ng’s Machine Learning Specialization, which has become a foundational resource for aspiring AI professionals. With a passion for education and innovation, Eddy continues to shape the future of AI learning and product management, empowering individuals to leverage artificial intelligence effectively in their careers.
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