Natural Language Processing

Natural Language Processing

The goal of Natural Language Processing (NLP) is to understand the semantics of text. Only when computers understand the real meaning of the text, can they take decisive action which must be the intended action.

In this course you will learn the mathematical fundamentals of NLP which includes Regular Expressions and the Vectorization process. Count vectorizer, cosine similarity and TF-IDF (Term Frequency Inverse Document Frequency) concepts will be covered. The semantics of text will be analyzed using Latent Semantic Analysis (LSA) and Latent Dirichlet Allocation (LDA).

Deep learning tools (TensorFlow + Keras) will be used to generate Word Embeddings like Word2Vec. Transformers will be covered which includes GPT (Generative Pre-Training) & BERT (Bi-Directional Encoder Representations Transformers).

Course Highlights:

• Fundamental mathematical analysis of NLP
• Tokenization using Regular Expressions
• Vectorization of words: Count Vectorizer + TF-IDF
• Cosine similarity between words
• Understand the meaning of text using Latent Semantic Analysis
• Topic Modeling using Latent Dirichlet Allocation
• Machine Learning: Naïve Bayes for text Classification
• Deep Learning: Word Embeddings Word2Vec + GloVe
• Deep Learning: Generating Neural Networks: GPT-1/2/3 (Generative Pre-Training)
• Deep Learning: NLP Analysis for Search Engines: BERT – (Bi-Directional Encoder Representations Transformers)

Course Learning Outcomes:

• Google Cloud Platform (GCP) and programming in Python
• Understanding of current machine learning models for NLP

Course Typically Offered: Onlin during the Winter and Summer academic quarters.

Software: Students will use Python to complete hands-on assignments. These tools are free and open-source.

Hardware: Students must have access to a web-enabled computer.

Prerequisites: CSE-40028 Introduction to Programming (Python) or equivalent knowledge and experience.

Next Step: After completing of this course, consider taking other courses in the Machine Learning Methods, Selected Topics in Artificial Intelligence, or Python Programming certificates.

Contact: For more information about this course, please contact unex-techdata@ucsd.edu.

Course Number: CSE-41344
Credit: 3.00 unit(s)
Related Certificate Programs: Machine Learning Methods, Selected Topics in Artificial Intelligence

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3/28/2023 - 5/27/2023

$745

Online

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• SECTION ID:

  171090

• CLASS TYPE:

  Online Asynchronous.
  
  This course is entirely web-based and to be completed asynchronously between the published course start and end dates. Synchronous attendance is NOT required.
  You will have access to your online course on the published start date OR 1 business day after your enrollment is confirmed if you enroll on or after the published start date.

• INSTRUCTOR:
  

  Pahwa, Ash, Founder, A+ Web Services

  Ash Pahwa, Ph.D., is an educator, author, entrepreneur, and technology visionary with three decades of industry and academic experience. He has founded several successful technology companies during his career, the latest of which is A+ Web Services. Dr. Pahwa earned his doctorate in Computer Science from the Illinois Institute of Technology in Chicago. He is listed in Who's Who in the Frontiers of Science and Technology . He is also a Google Certified Analytics Consultant. His expertise includes search engine optimization, web analytics, web programming, digital image processing, database management, digital video, and data storage technologies. In Industry, Dr. Pahwa has worked for General Electric, AT&T Bell Laboratories, Xerox Corporation, and Oracle. He founded CD-Gen...Read More

• TEXTBOOKS:

  No information available at this time.

• POLICIES:

  No refunds after: 4/3/2023.
  

• NOTE:

• DATE & LOCATION:

  3/28/2023 - 5/27/2023
  extensioncanvas.ucsd.edu
  You will have access to your course materials on the published start date OR 1 business day after your enrollment is confirmed if you enroll on or after the published start date.