Neural Models and Machine Translation
Completed by Niketa Kumari
January 22, 2026
17 hours (approximately)
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What you will learn
What You Will LearnBuild neural NLP models using RNNs, LSTMs, GRUs, and transformers for contextual text understanding and sequence-based tasks.
Apply attention mechanisms and encoder-decoder architectures to design effective machine translation and language generation systems.
Fine-tune pretrained models like BERT, RoBERTa, and MarianMT to perform multilingual NLP tasks with domain-specific accuracy.
Evaluate translation and classification systems using BLEU, ROUGE, and semantic similarity to improve performance and reliability.
Skills you will gain
- Category: Artificial Neural Networks
- Category: Large Language Modeling
- Category: Machine Learning
- Category: Fine-tuning
- Category: PyTorch (Machine Learning Library)
- Category: Artificial Intelligence and Machine Learning (AI/ML)
- Category: Deep Learning
- Category: Natural Language Processing
- Category: Recurrent Neural Networks (RNNs)
- Category: Transfer Learning
- Category: Model Evaluation
- Category: Model Training
