Implementing AI using Azure Machine Learning Services

on YouTube ↗53m

" summary

Live demo shows a classification pipeline built in Azure Machine Learning Studio that trains on a public diabetes CSV dataset, applies log z-score and min-max normalization, and splits data 70/30 for training and testing. Two classifiers run — logistic regression and a two‑class boosted decision tree — producing a confusion matrix, ROC-style true/false positive rates and accuracy numbers (roughly 0.7 vs 0.9). Data set is small (~200–300 rows), so models work but have limited generality.

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" chapters (10)

1. 0:00Start
2. 15:16Cloud Computing
3. 17:17Data Models
4. 18:43What Are the Technologies behind Ai
5. 27:13Example of a Machine Learning Algorithm
6. 27:59Difference between a Supervised and an Unsupervised Learning
7. 37:56Demo
8. 38:41Azure Machine Learning Studio
9. 40:27Data Distribution
10. 46:55Visualize a Data Set

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