Master Machine Learning with In-Depth Mathematical Insights
This comprehensive guide covers essential machine learning algorithms with a focus on the math that powers them. Topics include Simple and Multiple Linear Regression, Ridge/Lasso/Elastic Net Regression, Gradient Descent, Decision Trees, Ensemble Techniques, Random Forest, KNN, K-Means Clustering, Hierarchical Clustering, DBSCAN, and Support Vector Machines. With step-by-step breakdowns and real-world examples, this guide provides everything you need to confidently apply these algorithms and elevate your machine learning skills.
Geschreven voor
- Instelling
- Welingkar Institute of Management
- Vak
- BA101
Documentinformatie
- Geüpload op
- 18 september 2024
- Aantal pagina's
- 118
- Geschreven in
- 2023/2024
- Type
- College aantekeningen
- Docent(en)
- Ramnath krishnamurthy
- Bevat
- Alle colleges
Onderwerpen
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mastermachine learning with in depth mathematical