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Data science bookcamp : five Python projects / Leonard Apeltsin.

By: Material type: TextTextPublisher: Shelter Island, NY : Manning Publications Co., [2021]Description: xxvi, 676 pages : illustrations ; 24 cmContent type:
  • text
Media type:
  • unmediated
Carrier type:
  • volume
ISBN:
  • 9781617296253
Subject(s): DDC classification:
  • 006.312 APE  23
LOC classification:
  • QA76.9.D343 A3485 2021
Contents:
1. Computing probabilities using Python -- 2. Plotting probabilities using Matplotlib -- 3. Running random simulations in NumPy -- 4. Case study 1 solution -- 5. Basic probability and statistical analysis using SciPy -- 6. Making predictions using the central limit theorem and SciPy -- 7. Statistical hypothesis testing -- 8. Analyzing tables using Pandas -- 9. Case study 2 solution -- 10. Clustering data into groups -- 11. Geographic location visualization and analysis -- 12. Case study 3 solution -- 13. Measuring text similarities -- 14. Dimension reduction of matrix data -- 15. NLP analysis of large text datasets -- 16. Extracting text from web pages -- 17. Case study 4 solution -- 18. An introduction to graph theory and network analysis -- 19. Dynamic graph theory techniques for node ranking and social network analysis -- 20. Network-driven supervised machine learning -- 21. Training linear classifiers with logistic regression -- 22. Training nonlinear classifiers with decision tree techniques -- 23. Case study 5 solution.
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Holdings
Item type Current library Shelving location Call number Copy number Status Date due Barcode
Books Books CamTech Library STEM & Engineering 006.312 APE (Browse shelf(Opens below)) C.1 Available CamTech 000951

Subtitle on cover: five real-world Python projects.

Includes bibliographical references and index.

1. Computing probabilities using Python -- 2. Plotting probabilities using Matplotlib -- 3. Running random simulations in NumPy -- 4. Case study 1 solution -- 5. Basic probability and statistical analysis using SciPy -- 6. Making predictions using the central limit theorem and SciPy -- 7. Statistical hypothesis testing -- 8. Analyzing tables using Pandas -- 9. Case study 2 solution -- 10. Clustering data into groups -- 11. Geographic location visualization and analysis -- 12. Case study 3 solution -- 13. Measuring text similarities -- 14. Dimension reduction of matrix data -- 15. NLP analysis of large text datasets -- 16. Extracting text from web pages -- 17. Case study 4 solution -- 18. An introduction to graph theory and network analysis -- 19. Dynamic graph theory techniques for node ranking and social network analysis -- 20. Network-driven supervised machine learning -- 21. Training linear classifiers with logistic regression -- 22. Training nonlinear classifiers with decision tree techniques -- 23. Case study 5 solution.

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