Data Science and Predictive Analytics
portes grátis
Data Science and Predictive Analytics
Biomedical and Health Applications using R
Dinov, Ivo D.
Springer International Publishing AG
02/2023
918
Dura
Inglês
9783031174827
15 a 20 dias
Descrição não disponível.
Chapter 1 - Introduction.- Chapter 2: Basic Visualization and Exploratory Data Analytics.- Chapter 3: Linear Algebra, Matrix Computing and Regression Modeling.- Chapter 4: Linear and Nonlinear Dimensionality Reduction.- Chapter 5: Supervised Classification.- Chapter 6: Black Box Machine Learning Methods.- Chapter 7: Qualitative Learning Methods - Text Mining, Natural Language Processing, Apriori Association Rules Learning.- Chapter 8: Unsupervised Clustering.- Chapter 9: Model Performance Assessment, Validation, and Improvement.- Chapter 10: Specialized Machine Learning Topics.- Chapter 11: Variable Importance and Feature Selection.- Chapter 12: Big Longitudinal Data Analysis.- Chapter 13: Function Optimization.- Chapter 14: Deep Learning, Neural Networks.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
big data;R;statistical computing;predictive analytics;data science;health analytics;machine learning;statistical learning in R;hands-on machine learning;Big Data methods;data management;streaming;visualization;neural networks;controlled variable selection;text mining;natural language processing;cross-validation;deep learning
Chapter 1 - Introduction.- Chapter 2: Basic Visualization and Exploratory Data Analytics.- Chapter 3: Linear Algebra, Matrix Computing and Regression Modeling.- Chapter 4: Linear and Nonlinear Dimensionality Reduction.- Chapter 5: Supervised Classification.- Chapter 6: Black Box Machine Learning Methods.- Chapter 7: Qualitative Learning Methods - Text Mining, Natural Language Processing, Apriori Association Rules Learning.- Chapter 8: Unsupervised Clustering.- Chapter 9: Model Performance Assessment, Validation, and Improvement.- Chapter 10: Specialized Machine Learning Topics.- Chapter 11: Variable Importance and Feature Selection.- Chapter 12: Big Longitudinal Data Analysis.- Chapter 13: Function Optimization.- Chapter 14: Deep Learning, Neural Networks.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
big data;R;statistical computing;predictive analytics;data science;health analytics;machine learning;statistical learning in R;hands-on machine learning;Big Data methods;data management;streaming;visualization;neural networks;controlled variable selection;text mining;natural language processing;cross-validation;deep learning
