BE Honors (Data Science) SPPU

Click here for Subject: Statistics and Machine Learning

Presentations:

  1. Introduction to Data Science
  2. Data Objects and Attributes
  3. Data Science Process
  4. Statistical Descriptions of Data
  5. Data Science vs. BI
  6. Data Preprocessing Steps
  7. Probability
  8. Dataset
  9. Data Analytics
  10. K-Means Clustering
  11. Association Rule Mining
  12. Regression
  13. Classification
  14. Naive Bayes Classifier
  15. Data Exploration
  16. Linear Regression
  17. K-Nearest Neighbor
  18. Data Visualization
  19. Dashboard
  20. Data Visualization Types
  21. Data Modelling
  22. Study of Visualization Methods
  23. Data Visualization in R
  24. Data Visualization in Python
  25. Working with Keras
  26. Working with Tensorflow
  27. Apache Spark

Practical Programs:

  1. Practical No. 1 : Data Preprocessing
  2. Practical No. 2 : Probability Prediction
  3. Practical No. 3 : Classification and Regression
  4. Practical No. 4 : Data Visualization      Dataset