Gen AI Foundational Models for NLP & Language Understanding
This IBM course will teach you how to implement, train, and evaluate generative AI models for natural language processing (NLP). The course will help you acquire knowledge of NLP applications including document classification, language modeling, language translation, and fundamentals for building small and large language models.
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This IBM course will teach you how to implement, train, and evaluate generative AI models for natural language processing (NLP). The course will help you acquire knowledge of NLP applications including document classification, language modeling, language translation, and fundamentals for building small and large language models.
This IBM course will teach you how to implement, train, and evaluate generative AI models for natural language processing (NLP). The course will help you acquire knowledge of NLP applications including document classification, language modeling, language translation, and fundamentals for building small and large language models.
You will learn about converting words to features. You will understand one-hot encoding, bag-of-words, embedding, and embedding bags. You also will learn how Word2Vec embedding models are used for feature representation in text data.
You will implement these capabilities using PyTorch.
The course will teach you how to build, train, and optimize neural networks for document categorization. In addition, you will learn about the N-gram language model and sequence-to-sequence models. This course will help you evaluate the quality of generated text using metrics, such as BLEU.
You will practice what you learn using Hands-on Labs and perform tasks such as implementing document classification using torchtext in PyTorch. You will gain the skills to build and train a simple language model with a neural network to generate text and integrate pre-trained embedding models, such as word2vec, for text analysis and classification. In addition, you will apply your new skills to develop sequence-to-sequence models in PyTorch and perform tasks such as language translation.
What's inside
Syllabus
Fundamentals of Language Understanding
In this module, you will learn about one-hot encoding, bag-of-words, embeddings, and embedding bags. You will also gain knowledge of neural networks and their hyperparameters, cross-entropy loss, and optimization. You will then delve into the concept of language modeling with n-grams. The module also includes hands-on labs on document classification with PyTorch and building a simple language model with a neural network.
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Syllabus
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Activities
NLP Basics
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Review the fundamentals of NLP to strengthen your foundational understanding.
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Natural Language Processing
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Read introductory materials on NLP concepts and techniques.
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Complete practice exercises to reinforce your understanding of NLP basics.
Course Materials Compilation
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Organize your course materials for easy reference and review.
Show steps
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Gather and organize course notes, assignments, quizzes, and exams.
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Create a centralized repository for all materials.
NLP Discussion Group
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Engage with peers in discussions to enhance your understanding and retention of NLP concepts.
Browse courses on
NLP
Show steps
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Join or create a study group focused on NLP.
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Participate actively in discussions, sharing insights and asking questions.
Five other activities
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Hands-on Word2Vec
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Enhance your understanding of Word2Vec embeddings through guided tutorials.
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Word2Vec
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Follow online tutorials on Word2Vec implementation and usage.
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Experiment with different Word2Vec parameters to optimize performance.
NLP Expert Guidance
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Seek guidance from experienced NLP professionals to deepen your understanding and career development.
Browse courses on
NLP
Show steps
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Identify NLP experts through online platforms or professional networks.
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Reach out to potential mentors and request guidance.
Sequence-to-Sequence Practice
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Master sequence-to-sequence models through consistent practice to improve accuracy and efficiency.
Show steps
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Solve coding problems on sequence-to-sequence tasks.
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Participate in online coding challenges to test your skills.
Natural Language Classifier
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Solidify your knowledge of document classification by building a classifier from scratch.
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Document Classification
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Choose a dataset and preprocess the text data.
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Define a neural network model for document classification.
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Train and evaluate your model on the chosen dataset.
Chatbot Development
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Gain practical experience in NLP by developing a chatbot using the skills learned in the course.
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Chatbots
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Design the chatbot's conversation flow and user interface.
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Implement the chatbot's natural language processing capabilities using course-learned techniques.
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Test and refine the chatbot's performance through user interaction.
NLP Basics
Show steps
Review the fundamentals of NLP to strengthen your foundational understanding.
Browse courses on
Natural Language Processing
Show steps
- Read introductory materials on NLP concepts and techniques.
- Complete practice exercises to reinforce your understanding of NLP basics.
Course Materials Compilation
Show steps
Organize your course materials for easy reference and review.
Show steps
- Gather and organize course notes, assignments, quizzes, and exams.
- Create a centralized repository for all materials.
NLP Discussion Group
Show steps
Engage with peers in discussions to enhance your understanding and retention of NLP concepts.
Browse courses on
NLP
Show steps
- Join or create a study group focused on NLP.
- Participate actively in discussions, sharing insights and asking questions.
Hands-on Word2Vec
Show steps
Enhance your understanding of Word2Vec embeddings through guided tutorials.
Browse courses on
Word2Vec
Show steps
- Follow online tutorials on Word2Vec implementation and usage.
- Experiment with different Word2Vec parameters to optimize performance.
NLP Expert Guidance
Show steps
Seek guidance from experienced NLP professionals to deepen your understanding and career development.
Browse courses on
NLP
Show steps
- Identify NLP experts through online platforms or professional networks.
- Reach out to potential mentors and request guidance.
Sequence-to-Sequence Practice
Show steps
Master sequence-to-sequence models through consistent practice to improve accuracy and efficiency.
Show steps
- Solve coding problems on sequence-to-sequence tasks.
- Participate in online coding challenges to test your skills.
Natural Language Classifier
Show steps
Solidify your knowledge of document classification by building a classifier from scratch.
Browse courses on
Document Classification
Show steps
- Choose a dataset and preprocess the text data.
- Define a neural network model for document classification.
- Train and evaluate your model on the chosen dataset.
Chatbot Development
Show steps
Gain practical experience in NLP by developing a chatbot using the skills learned in the course.
Browse courses on
Chatbots
Show steps
- Design the chatbot's conversation flow and user interface.
- Implement the chatbot's natural language processing capabilities using course-learned techniques.
- Test and refine the chatbot's performance through user interaction.
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