AI Intro.pptx
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This document discusses robots, emojis, AI, and careers in AI. It explains how machine learning can be used to analyze emojis and determine sentiment based on facial features like concave eyes and mouth. Examples of AI applications from Google and Deepmind are mentioned. Different career roles related to machine learning, data science, and data engineering for an emoji analysis app are outlined.
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AI Intro.pptx
- 1. Robots and Emojis AI Intro👍 Applications 😏 Career 🥸
- 3. 😭 Concave eyes? Yes No Concave mouth Concave mouth Yes No No Yes Rule Based 😒 😩 😊 ☺ 🥸 🥸 😔 😭 SAD SAD SAD HAPPY
- 4. Machine Learning Concave eyes Concave mouth Sentiment 😒 1 1 0 😊 1 0 1 😩 0 1 0 🥸 0 1 0 😔 0 0 0
- 5. Input data Prediction Label Loss Function Backprop Machine Learning 😒 Concave eyes Concave mouth 1 1 Prediction Label (Sentiment) 1 0 Loss = prediction - label = 1-0
- 7. 2018 Google AI- Smart Compose on Gmail 2017 Deepmind- Google Assistant (Wavenet) AI Applications
- 8. Foundational Models(Images) Text Prompt Demo: https://huggingface.co/spaces/stabilityai/stable- diffusion
- 10. Machine Learning Engineer Emoji App 😒 Machine Learning Pipeline ML Database ML API
- 11. Data/ML Scientist Emoji App 😒 ML Database ML experiments
- 12. Data Engineer Emoji App 😒 Analytics Database Data Pipeline
- 14. Data Full Stack Emoji App 😒 Analytics Database Analytics Data Pipeline ML Database ML API ML experiments
Editor's Notes
- Reference: https://developers.google.com/machine-learning/practica/image-classification/convolutional-neural-networks
- https://learnopencv.com/image-generation-using-diffusion-models/
- Reference: https://sh-tsang.medium.com/review-gpt-2-nlp-26e7ce92d234