Gen AI Foundational Models for NLP & Language Understanding
Completed by Muhammad Umer Yousaf
December 12, 2024
9 hours (approximately)
Muhammad Umer Yousaf's account is verified. Coursera certifies their successful completion of Gen AI Foundational Models for NLP & Language Understanding
What you will learn
Explain how one-hot encoding, bag-of-words, embeddings, and embedding bags transform text into numerical features for NLP models
Implement Word2Vec models using CBOW and Skip-gram architectures to generate contextual word embeddings
Develop and train neural network-based language models using statistical N-Grams and feedforward architectures
Build sequence-to-sequence models with encoder–decoder RNNs for tasks such as machine translation and sequence transformation
Skills you will gain
- Category: Natural Language Processing
- Category: Artificial Neural Networks
- Category: Embeddings
- Category: PyTorch (Machine Learning Library)
- Category: Large Language Modeling
- Category: Data Preprocessing
- Category: Classification Algorithms
- Category: Recurrent Neural Networks (RNNs)
- Category: Data Ethics
- Category: Model Evaluation
- Category: Transfer Learning
- Category: Generative AI
