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<<<PE206>>> Data science Lab

  1. Basic data manipulation programs in Python
  2. Basic programs for visualizing data
  3. Programs to explore and infer data
  4. Apply Linear Regression to solve a data science problem
  5. Apply SVM classification techniques
  6. Apply Decision tree
  7. Apply clustering techniques
  8. Visualize data using any plotting framework

    Applications

i. Flower type classification based on available attributes using Iris dataset ii. Passengers survival classification using titanic dataset iii.Loan prediction using Credit approval dataset iv. Sales prediction using Bigmart dataset v. Sentiment analysis using twitter dataset vi.Hand written digit recognition using MNIST dataset

\hfill Total Periods: 45

TEXT BOOKS

  1. Jake VanderPlas, “Python Data Science Handbook ESSENTIAL TOOLS FOR WORKING WITH DATA ”,

O’Reilly Media, Inc., 2016

  1. Joel Grus, “ Data Science from Scratch FIRST PRINCIPLES WITH PYTHON ”, O’Reilly Media, Inc., 2015
  2. DAVY CIELEN, ARNO D. B. MEYSMAN, MOHAMED ALI, “Introducing Data Science BIG DATA, MACHINE LEARNING, AND MORE, USING PYTHON TOOLS ”,

Manning Publications Co, 2016.

  1. Jonathan Dinu, “Foundations of Data Science: A Practical Introduction to Data Science with Python”, Addison-wesley Data & Analytics Series, 2016.
  2. Cathy O’Neil, Rachel Schutt. “Doing Data Science, Straight Talk From The Frontline”, O’Reilly, 2014.