What will you learn in this Natural Language Processing with Sequence Models Course
-
Train neural networks with word embeddings to perform sentiment analysis of tweets.
-
Generate synthetic text using Gated Recurrent Unit (GRU) language models.
-
Implement Named Entity Recognition (NER) using Long Short-Term Memory (LSTM) networks.
-
Utilize Siamese LSTM networks to identify duplicate questions in datasets.
Program Overview
1. Neural Networks for Sentiment Analysis
⏳ 5 hours
Learn about deep neural networks and build a tweet classifier to determine sentiment polarity
2. Recurrent Neural Networks for Language Modeling
⏳ 5 hours
Understand the limitations of traditional language models and implement RNNs and GRUs to generate text sequences.
3. LSTMs and Named Entity Recognition
⏳ 5 hours
Explore LSTM networks to address the vanishing gradient problem and apply them to extract entities from text.
4. Siamese Networks for Duplicate Question Detection
⏳ 5 hours
Implement Siamese LSTM networks to identify semantically similar questions, enhancing information retrieval systems
Get certificate
Job Outlook
-
Prepares learners for roles such as NLP Engineer, Machine Learning Engineer, and Data Scientist.
-
Applicable in industries like technology, healthcare, finance, and e-commerce.
-
Enhances employability by providing practical skills in sequence modeling and natural language processing.
-
Supports career advancement in fields requiring expertise in deep learning and NLP applications.
Explore More Learning Paths
Deepen your understanding of NLP and sequence modeling with these curated courses designed to advance your skills in building intelligent language-based applications.
Related Courses
-
Natural Language Processing Specialization Course – Gain a comprehensive foundation in NLP, including text processing, sentiment analysis, and machine learning techniques for language data.
-
Natural Language Processing with Attention Models Course – Explore advanced NLP techniques using attention mechanisms to improve model performance on complex language tasks.
-
Natural Language Processing in TensorFlow Course – Learn to implement NLP models in TensorFlow, focusing on practical applications like text classification and sequence modeling.
Related Reading
Gain deeper insight into managing and analyzing data for intelligent applications:
-
What Is Data Management? – Understand how structured data management underpins effective NLP model development and real-world deployment.
