Section A - An introduction to No-Code AI
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1. What is AI (2:13)
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2. What is Machine Learning (2:04)
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3. What is Supervised Learning (2:18)
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4. What is Time Series (2:04)
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5. Supervised Learning Problems vs. Time Series Problems (1:33)
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6. Type of ML Problems (0:52)
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7. What is No-code AI (2:30)
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8. Possibilities of No-code AI (2:54)
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9. What is Obviously AI (1:32)
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10. Intro to Obviously AI AutoML (1:32)
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11. Intro to Obviously AI Time Series (1:50)
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12. How it Works (1:42)
Section B - Adding Data
Section C - Running Predictions
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Auto ML: Making your first AutoML model (3:20)
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Auto ML: Predicting Outcomes (3:03)
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AutoML: Understanding Factors that Affect Predictions (3:00)
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Auto ML: Making Predictions Via Batch (4:15)
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Auto ML: Understanding Tech Specs (3:28)
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Auto ML: Updating your model (2:20)
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Auto ML: Sharing Your Model (2:31)
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Time Series: Predicting Outcomes (2:07)
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Time Series: Evaluating Model Performance (3:14)
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Time Series: Understanding Tech Specs (2:39)
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Time Series - Updating your model (1:42)
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Time Series: Updating Your Model (2:00)
