Machine Learning Using R : With Time Series and Industry-Based Use Cases in R

Machine Learning Using R With Time Series and Industry-Based Use Cases in R

Examine the latest technological advancements in building a scalable machine-learning model with big data using R. This second edition shows you how to work with a machine-learning algorithm and use it to build a ML model from raw data. You will see how to use R programming with TensorFlow, thus avo...

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Detalles Bibliográficos
Autores principales: Ramasubramanian, Karthik. author (author), Singh, Abhishek. author
Formato: Libro electrónico
Idioma:Inglés
Publicado: Berkeley, CA : Apress 2019.
Edición:2nd ed. 2019.
Materias:
Artificial intelligence.
Open source software.
Computer programming.
Programming languages (Electronic computers).
R (Computer program language).
Artificial Intelligence.
Open Source.
Programming Languages, Compilers, Interpreters.
Ver en Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009630512706719
Tabla de Contenidos:
  • Chapter 1: Introduction to Machine Learning
  • Chapter 2: Data Exploration and Preparation
  • Chapter 3: Sampling and Resampling Techniques
  • Chapter 4: Visualization of Data
  • Chapter 5: Feature Engineering
  • Chapter 6: Machine Learning Models: Theory and Practice
  • Chapter 7: Machine Learning Model Evaluation
  • Chapter 8: Model Performance Improvement
  • Chapter 9: Time Series Modelling
  • Chapter 10: Scalable Machine Learning and related technology
  • Chapter 11: Introduction to Deep Learning Models using Keras and TensorFlow.

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