Pro Machine Learning Algorithms : A Hands-On Approach to Implementing Algorithms in Python and R

Pro Machine Learning Algorithms A Hands-On Approach to Implementing Algorithms in Python and R

Bridge the gap between a high-level understanding of how an algorithm works and knowing the nuts and bolts to tune your models better. This book will give you the confidence and skills when developing all the major machine learning models. In Pro Machine Learning Algorithms, you will first develop t...

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Bibliographic Details
Main Author: Ayyadevara, V Kishore. author (author)
Format: eBook
Language:Inglés
Published: Berkeley, CA : Apress 2018.
Edition:1st ed. 2018.
Subjects:
Artificial intelligence.
Python (Computer program language).
Big data.
Open source software.
Computer programming.
R (Computer program language).
Artificial Intelligence.
Python.
Big Data.
Open Source.
See on Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009630079706719
Table of Contents:
  • Chapter 1: Basics of Machine Learning
  • Chapter 2: Linear regression
  • Chapter 3: Logistic regression
  • Chapter 4: Decision tree
  • Chapter 5: Random forest
  • Chapter 6: GBM
  • Chapter 7: Neural network
  • Chapter 8: word2vec
  • Chapter 9: Convolutional neural network
  • Chapter 10: Recurrent Neural Network
  • Chapter 11: Clustering
  • Chapter 12: PCA
  • Chapter 13: Recommender systems
  • Chapter 14: Implementing algorithms in the cloud.

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