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Hands-On Data Science with Anaconda

You're reading from  Hands-On Data Science with Anaconda

Product type Book
Published in May 2018
Publisher Packt
ISBN-13 9781788831192
Pages 364 pages
Edition 1st Edition
Languages
Authors (2):
Yuxing Yan Yuxing Yan
Profile icon Yuxing Yan
James Yan James Yan
Profile icon James Yan
View More author details

Table of Contents (15) Chapters

Preface Ecosystem of Anaconda Anaconda Installation Data Basics Data Visualization Statistical Modeling in Anaconda Managing Packages Optimization in Anaconda Unsupervised Learning in Anaconda Supervised Learning in Anaconda Predictive Data Analytics – Modeling and Validation Anaconda Cloud Distributed Computing, Parallel Computing, and HPCC References Other Books You May Enjoy

Review questions and exercises

  1. What does unsupervised learning mean?
  2. What is the major difference between unsupervised learning and supervised learning?
  3. How do we install the Python package sklearn?
  4. Discuss the relationship between distance and clustering classification.
  5. What does Bayes classification mean?
  6. Find out the related functions for Bayes classification in R, Python, Octave, and Julia.

  1. How many R packages are installed after you run the following three lines of R code?
>install.packages("ctv")
>library("ctv")
>install.views("MachineLearning")
  1. Download the IBM monthly data from Yahoo!Finance, https://finance.yahoo.com . Then run a Fama-French-Carhart four factor model by using Python. The 4-factor model is given here:

The Python dataset related to those 4-factors can be downloaded from the author's website at http:/...

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