"Intro to AI for software engineers Using go-learn"
summary
Demo uses go-learn to implement linear regression in about 15 lines, then trains a decision tree on 700,000 labeled words with a 70/30 train/test split, randomized before splitting. It shows CSV import, feature engineering for names, model.fit/predict calls, reports precision ≈0.69 with confusion-matrix breakdown, and explains tuning via stochastic node weight. Code examples live in the go-learn examples directory and are runnable as shown.
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chapters (14)
- 0:00Start
- 1:38What Is Machine Learning
- 2:45What Does Machine Learning Do
- 3:16Pattern Recognition
- 4:21Supervised Learning
- 4:56Unsupervised Learning
- 5:18Reinforcement Learning
- 6:10Linear Regression
- 7:24Logistic Regression
- 7:48Implementation
- 9:37Decision Tree
- 14:12Confusion Matrix
- 14:28What a Confusion Matrix
- 19:09Machine Learning Crash Course
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