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Fundamentals of Data Science Part III Jared M Maruskin
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Fundamentals of Data Science Part III
Jared M Maruskin
In Part III of this series, we cover the fundamentals of machine learning, focusing on: validation methodology (reprint)nearest neighbor, k-means, support vector machines, principal component analysistree-based methods: decision trees, bagging, random forest, boosting, XGBoostartificial neural networks and deep learningreinforcement learning
The focus is on algorithmic development and programming. We code each technique from scratch in Python, using an object-oriented approach.
| Mediji | Grāmatas Paperback Book (Grāmata ar mīksto vāku un līmēto muguru) |
| Izlaists | 2022. gada 29. aprīlis |
| ISBN13 | 9781941043134 |
| Izdevēji | Cayenne Canyon Press |
| Lapas | 316 |
| Izmēri | 156 × 234 × 17 mm · 444 g |
| Valoda | Angļu |
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