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Machine Learning Curriculum

1. What is Machine Learning
2. Use Teachable Machine: build a classification model
3. Use Google Colab and TensorFlow: build regression and classification models​​

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Teachable Machine (Day 1)
Intro to Machine Learning
​Students will learn about:

• Supervised learning
  
• Unsupervised learning
  
• Reinforcement Learning

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Teachable Machine
​Students will learn how to:

• Build image classification models (cat and dog)
  
• Build audio classification models

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Lemonade (Day 2)
​Lemonade Project
Students will learn how to:

• Use Tensorflow and Python
• Build a supervised regression learning model
• Input one independent variable​​

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Boston Housing (Day 3)
Boston Housing Project
Students will learn how to:

• Build a supervised regression learning model
• Input multiple independent variables
• Analyze reasons for loss

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Hidden Layers (Day 4)
Hidden Layers Project
Students will learn how to:

• Code deep learning with hidden layers
  
• Create more accurate models with smaller loss
  

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Iris Flower (Day 5)
Iris Flower Project
Students will learn how to:

• Build supervised classification learning models 
  
• Code categorization in TensorFlow
  
• Output multiple dependent variable
  

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Students may be given homework each week.