Exploring Artificial Intelligence and Computer Vision in Industries

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Delve into the world of Artificial Intelligence (AI) with real industry cases. Learn about Natural Language Processing (NLP) and Computer Vision through examples and practical exercises. Understand NLP's use of probability statistics, intent, utterance, entity, and session elements. Discover how Computer Vision uses AI for trend-based predictions and image identification techniques like pooling and convolution.


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  1. Introduction to Artificial Intelligence (AI) and Real Cases from Industries Name:

  2. NLP(12/14) (12/14)

  3. My notes of NLP Base probability statistics Purpose enable computers to understand human s language Usage figure out the intent of the users and give response Elements that NLP relies on 1. Intent 2. Utterance 3. Entity 4. Session

  4. Screenshots of the hand-on practice Ex.1 Google Trans.

  5. Screenshots of the hand-on practice Ex.2 Simplify / Visuailize the Keyword

  6. Screenshots of the hand-on practice Ex.3 Sentimental Analysis

  7. Screenshots of the hand-on practice Ex.4 Python Word Cloud

  8. Screenshots of the hand-on practice Ex.5 Multiple Language Sentimental Analysis

  9. Computer Vision (12/21)

  10. My notes of computer vision Base AI makes predictions based on the founded trend of data How AI identify a 2D picture? 1. Divide into blocks, and set grey value for each 2. Use the linear-relationship to solve the identification Improve the accuracy reduce the scale (CNN) 1. Pooling (Quantity) combine the data clusters into one single cluster 2. Convolution (Quality) extract targeted features and filter out unnecessary noise

  11. Screenshots of the hand-on practice Number Prediction

  12. Screenshots of the hand-on practice Pooling

  13. Screenshots of the hand-on practice Convolution

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