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Obviously AI No Code University
Section A - An introduction to No-Code AI
1. What is AI (2:13)
2. What is Machine Learning (2:04)
3. What is Supervised Learning (2:18)
4. What is Time Series (2:04)
5. Supervised Learning Problems vs. Time Series Problems (1:33)
6. Type of ML Problems (0:52)
7. What is No-code AI (2:30)
8. Possibilities of No-code AI (2:54)
9. What is Obviously AI (1:32)
10. Intro to Obviously AI AutoML (1:32)
11. Intro to Obviously AI Time Series (1:50)
12. How it Works (1:42)
Section B - Adding Data
Adding Data: Uploading Spreadsheets (1:40)
Adding Data: Connecting to a database (2:11)
Adding Data : Connecting to Service (2:15)
Adding Data: Sample Datasets and Datastore (2:15)
Section C - Running Predictions
Auto ML: Making your first AutoML model (3:20)
Auto ML: Predicting Outcomes (3:03)
AutoML: Understanding Factors that Affect Predictions (3:00)
Auto ML: Making Predictions Via Batch (4:15)
Auto ML: Understanding Tech Specs (3:28)
Auto ML: Updating your model (2:20)
Auto ML: Sharing Your Model (2:31)
Time Series: Predicting Outcomes (2:07)
Time Series: Evaluating Model Performance (3:14)
Time Series: Understanding Tech Specs (2:39)
Time Series - Updating your model (1:42)
Time Series: Updating Your Model (2:00)
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5. Supervised Learning Problems vs. Time Series Problems
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