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CS685: Advanced Natural Language Processing

  • Course level: All Levels

Description

Natural Language Processing (NLP) will be taught by an experienced specialist in this course. 

Giving machines the ability to interpret unstructured data extracted from natural language has a lot of potentials. In this course, I cover a wide range of NLP subjects. I explain NLP ideas in a straightforward manner, including examples in Python utilizing libraries such as NLTK, spaCy, and TensorFlow. I also talk about text pre-processing, text classification, text summarization, topic modeling, and word embeddings, among other things. I also discuss NLP applications in a variety of fields, such as healthcare and finance.

This course is for 
beginners who wish to learn about Natural Language Processing from an experienced professional in a hands-on manner. Python programmers who want to learn more about natural language processing.

What Will I Learn?

  • Natural Language Processing: Concepts and Applications
  • Python, TensorFlow, spaCy, and gensim libraries are used to implement Natural Language Processing techniques.

Topics for this course

23 Lessons

UMass CS685 (Advanced NLP): course introduction

UMass CS685 (Advanced NLP): Language modeling00:00:00
UMass CS685 (Advanced NLP): Neural language models00:00:00
UMass CS685 (Advanced NLP): Final projects00:00:00
UMass CS685 (Advanced NLP): Backpropagation00:00:00
UMass CS685 (Advanced NLP): Implementing a neural language model in PyTorch00:00:00
UMass CS685 (Advanced NLP): Attention mechanisms00:00:00
UMass CS685 (Advanced NLP): Transformers and sequence-to-sequence models00:00:00
UMass CS685 (Advanced NLP): Transfer learning for NLP00:00:00
UMass CS685 (Advanced NLP): BERT00:00:00
UMass CS685 (Advanced NLP): Scaling up language modeling & GPT-300:00:00
UMass CS685 (Advanced NLP): Text generation decoding and evaluation00:00:00
UMass CS685 (Advanced NLP): Paraphrase generation00:00:00
UMass CS685 (Advanced NLP): Crowdsourced text data collection00:00:00
UMass CS685 (Advanced NLP): Model distillation and security threats00:00:00
UMass CS685 (Advanced NLP): Retrieval-augmented language models00:00:00
UMass CS685 (Advanced NLP): Implementing a Transformer00:00:00
UMass CS685 (Advanced NLP): vision + language00:00:00
UMass CS685 (Advanced NLP): exam review00:00:00
UMass CS685 (Advanced NLP): Intermediate fine-tuning00:00:00
UMass CS685 (Advanced NLP): ethics in NLP00:00:00
UMass CS685 (Advanced NLP): probe tasks00:00:00
UMass CS685 (Advanced NLP): semantic parsing00:00:00
UMass CS685 (Advanced NLP): commonsense reasoning (guest lecture by Lorraine Li)00:00:00
Free

Enrolment validity: Lifetime

Requirements

  • Python knowledge is required.
  • Machine learning knowledge at a basic level