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Ebook Understanding machine learning: From theory to algorithms - Part 1
Part 1 of ebook "Understanding machine learning: From theory to algorithms" provides readers with contents including: foundations; from theory to algorithms; a formal learning model; learning via uniform convergence; the bias-complexity tradeoff; linear predictors; model selection and validation; convex learning problems; support vector machines; multiclass, ranking, and complex prediction problems;...
284 p umt 23/12/2023 14 0
Từ khóa: Understanding machine learning, Machine learning algorithms, Formal learning model, The bias-complexity tradeoff, Linear predictors, Convex learning problems, Support vector machines
Ebook Understanding machine learning: From theory to algorithms - Part 2
Continued part 1, part 2 of ebook "Understanding machine learning: From theory to algorithms" provides readers with contents including: additional learning models; advanced theory; dimensionality reduction; generative models; feature selection and generation; rademacher complexities; proof of the fundamental theorem of learning theory; multiclass learnability; compression bounds;...
165 p umt 23/12/2023 14 0
Từ khóa: Understanding machine learning, Machine learning algorithms, Additional learning models, Advanced theory, Dimensionality reduction, Rademacher complexities, Multiclass learnability
Ebook Machine learning algorithms: Part 1
Ebook Machine learning algorithms: Part 1 presents the following content: Chapter 1: a gentle introduction to machine learning, chapter 2: important elements in machine learning, chapter 3: feature selection and feature engineering, chapter 4: linear regression, chapter 5: logistic regression, chapter 6: naive bayes, chapter 7: support vector machines.
169 p umt 12/06/2023 17 0
Từ khóa: Ebook Machine learning algorithms, Machine learning algorithms, Machine learning, Feature engineering, Linear regression, Logistic regression
Ebook Machine learning algorithms: Part 2
Ebook Machine learning algorithms: Part 2 presents the following content: Chapter 8: decision trees and ensemble learning, chapter 9: clustering fundamentals, chapter 10: hierarchical clustering, chapter 11: introduction to recommendation systems, chapter 12: introduction to natural language processing, chapter 13: topic modeling and sentiment analysis in NLP, chapter 14: a brief introduction to deep learning and tensorflow, chapter 15:...
184 p umt 12/06/2023 11 0
Từ khóa: Ebook Machine learning algorithms, Machine learning algorithms, Clustering fundamentals, Hierarchical clustering, Natural language processing, Sentiment analysis in NLP
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