Share
Practical Machine Learning in R (in English)
Mike Chapple
(Author)
·
Fred Nwanganga
(Author)
·
Wiley
· Paperback
Practical Machine Learning in R (in English) - Nwanganga, Fred ; Chapple, Mike
$ 39.54
$ 65.90
You save: $ 26.36
Choose the list to add your product or create one New List
✓ Product added successfully to the Wishlist.
Go to My Wishlists
Origin: United Kingdom
(Import costs included in the price)
It will be shipped from our warehouse between
Friday, May 24 and
Monday, June 03.
You will receive it anywhere in United States between 1 and 3 business days after shipment.
Synopsis "Practical Machine Learning in R (in English)"
Guides professionals and students through the rapidly growing field of machine learning with hands-on examples in the popular R programming language Machine learning--a branch of Artificial Intelligence (AI) which enables computers to improve their results and learn new approaches without explicit instructions--allows organizations to reveal patterns in their data and incorporate predictive analytics into their decision-making process. Practical Machine Learning in R provides a hands-on approach to solving business problems with intelligent, self-learning computer algorithms. Bestselling author and data analytics experts Fred Nwanganga and Mike Chapple explain what machine learning is, demonstrate its organizational benefits, and provide hands-on examples created in the R programming language. A perfect guide for professional self-taught learners or students in an introductory machine learning course, this reader-friendly book illustrates the numerous real-world business uses of machine learning approaches. Clear and detailed chapters cover data wrangling, R programming with the popular RStudio tool, classification and regression techniques, performance evaluation, and more. Explores data management techniques, including data collection, exploration and dimensionality reduction Covers unsupervised learning, where readers identify and summarize patterns using approaches such as apriori, eclat and clustering Describes the principles behind the Nearest Neighbor, Decision Tree and Naive Bayes classification techniques Explains how to evaluate and choose the right model, as well as how to improve model performance using ensemble methods such as Random Forest and XGBoost Practical Machine Learning in R is a must-have guide for business analysts, data scientists, and other professionals interested in leveraging the power of AI to solve business problems, as well as students and independent learners seeking to enter the field.
- 0% (0)
- 0% (0)
- 0% (0)
- 0% (0)
- 0% (0)
All books in our catalog are Original.
The book is written in English.
The binding of this edition is Paperback.
✓ Producto agregado correctamente al carro, Ir a Pagar.
