Skip to content

krishnac7/DSX_HandsOn-master

Repository files navigation

Note:

Tested on Python 2.7 with spark 2.0

  • Run the below line of code to install 0.18 of scikitlearn
!pip install scikit-learn==0.18

Classification

  • Classification classification-12Liner consists of a shortened version of IRIS classifier with no evaluation
  • Classification Simple outputs a related image basing on the classification of the flower
  • Classification_Evaluation contains the Complete version of Basic IRIS data classification along with performance evaluation and algorithm comparision
  • MNIST Simple classifies random test images of hand written digits from MNIST Dataset into respective classes of 0-9

Regression

  • Regression_realestate uses Linear regression to predict Real estate prices based on a dataset included in RealestateData.csv
  • Regression_tv predicts which of the two Tv series flash or Arrow gets most veiwership based on the data from veiwershipData.csv

Importing Notebooks onto DSX

From From URL

  • Copy the URL of the python notebook File
  • Click on From URL Tab
  • Give your project a name and paste the copied url in Notebook URL Field

From File

  • Download the gitHub Repo
  • Click on From File Tab
  • Give your notebook a name and click browse button to import your .ipnyb file

Accessing DataFiles

  • Click on add data assets from the project home screen
  • Import your .csv data file
  • From within the notebook, click the Find and add Data menu item on the top right
  • Find your dataset and select Insert Pandas Dataframe
  • use the assigned Data variable which can be seen in the second-bottom most line of the inserted code

About

No description, website, or topics provided.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published