Skip to content

Probability and Statistics Using Python Data Science Masters Course at UCSD (DSE 210)

Notifications You must be signed in to change notification settings

mGalarnyk/DSE210_Probability_Statistics_Python

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

DSE210_Probability_Statistics_Python

Looks best on google chrome. Probability and Statistics Using Python: Data Science Masters Course (DSE 210). Highly similar to UCSD's "CSE 250B. Principles of Artificial Intelligence: Learning Algorithms" course. Most of the early portions of the class are worksheet based, but the later portions are mostly in ipython notebook (numpy, sklearn, pandas).

IPython Notebooks for Assignments (From Newest to Oldest)

  • [Hypothesis testing](https://github.com/mGalarnyk/DSE210_Probability_Statistics_Python/blob/master/10_Hypothesis_Testing.ipynb) (1, 2, 6, 7, 8, 9, 10)
  • [Sampling](https://github.com/mGalarnyk/DSE210_Probability_Statistics_Python/blob/master/9_Sampling.ipynb) (1, 3, 5, 8, 9, 10, 11)
  • [Matrix factorization](https://github.com/mGalarnyk/DSE210_Probability_Statistics_Python/blob/master/8_Matrix_Factorization.ipynb) # 1,2,3,4 (PCA Projection, python),5 (PCA Projection, python)
  • [Clustering](https://github.com/mGalarnyk/DSE210_Probability_Statistics_Python/blob/master/7_Clustering.ipynb)
  • [Generative models 2](https://github.com/mGalarnyk/DSE210_Probability_Statistics_Python/blob/master/6_Generative_Models_number_9-FINAL.ipynb) Gaussian Classifier
  • [Generative models 1](https://github.com/mGalarnyk/DSE210_Probability_Statistics_Python/blob/master/5_Generative_Models_I_Class_Generators.ipynb) (object oriented, next up is pandas and sql)
  • [Random variable, expectation, and variance](https://github.com/mGalarnyk/DSE210_Probability_Statistics_Python/blob/master/4_RandomVariable_Expectation_Variance.ipynb) (1,2,3,6,7a,7c,8,12)
  • [Multiple events, conditioning, and independence](https://github.com/mGalarnyk/DSE210_Probability_Statistics_Python/blob/master/3_Multiple_events_%20conditioning_and_independence.ipynb) (1,2,3,5,6,10,15a,16)
  • [Probability spaces](https://github.com/mGalarnyk/DSE210_Probability_Statistics_Python/blob/master/2_Probability_spaces.ipynb) (1a,1b,1e,2,3,4a,5,6,7,14,16)
  • [Sets and counting](https://github.com/mGalarnyk/DSE210_Probability_Statistics_Python/blob/master/1_Sets_and_Counting_mGalarnyk.ipynb) (1,2,3,4,5,6)
  • Worksheets (From Newest to Oldest)

  • [Hypothesis testing](https://github.com/mGalarnyk/DSE210_Probability_Statistics_Python/blob/master/worksheets/worksheet10Hypothesis_testing.pdf) (1, 2, 6, 7, 8, 9, 10)
  • [Sampling](https://github.com/mGalarnyk/DSE210_Probability_Statistics_Python/blob/master/worksheets/worksheet9Sampling.pdf) (1, 3, 5, 8, 9, 10, 11)
  • [Matrix factorization](https://github.com/mGalarnyk/DSE210_Probability_Statistics_Python/blob/master/worksheets/worksheet8Matrix_factorization.pdf) (1,2,3,4,5)
  • [Clustering](https://github.com/mGalarnyk/DSE210_Probability_Statistics_Python/blob/master/worksheets/worksheet7Clustering.pdf) (all)
  • [Generative models 2](https://github.com/mGalarnyk/DSE210_Probability_Statistics_Python/blob/master/worksheets/worksheet6GenerativeModels2.pdf) (#9 python based Gaussian Classifier)
  • [Generative models 1](https://github.com/mGalarnyk/DSE210_Probability_Statistics_Python/blob/master/worksheets/worksheet5Generative_models_1.pdf) (all)
  • [Random variable, expectation, and variance](https://github.com/mGalarnyk/DSE210_Probability_Statistics_Python/blob/master/worksheets/worksheet4Random_variable_expectation_and_variance.pdf) (1,2,3,6,7a,7c,8,12)
  • [Multiple events, conditioning, and independence](https://github.com/mGalarnyk/DSE210_Probability_Statistics_Python/blob/master/worksheets/worksheet3_Multiple_events_%20conditioning_and_independence.pdf) (1,2,3,5,6,10,15a,16)
  • [Probability spaces](https://github.com/mGalarnyk/DSE210_Probability_Statistics_Python/blob/master/worksheets/worksheet2_Probability_spaces.pdf) (1a,1b,1e,2,3,4a,5,6,7,14,16)
  • [Sets and counting](https://github.com/mGalarnyk/DSE210_Probability_Statistics_Python/blob/master/worksheets/worksheet1_Sets_and_counting.pdf) (1,2,3,4,5,6)
  • Other (Iris Dataset plus other scratch worksheet)

  • [K-Means, PCA, and Dendrogram on the Animals with Attributes Dataset](https://github.com/mGalarnyk/DSE210_Probability_Statistics_Python/blob/master/K-Means%2C%20PCA%2C%20and%20Dendrogram%20on%20the%20Animals%20with%20Attributes%20Dataset.ipynb)
  • [Iris Dataset](https://github.com/mGalarnyk/DSE210_Probability_Statistics_Python/blob/master/IRIS%20data%20set.ipynb)
  • [Scratch stats problems](https://github.com/mGalarnyk/DSE210_Probability_Statistics_Python/blob/master/Other_worksheet.pdf)
  • About

    Probability and Statistics Using Python Data Science Masters Course at UCSD (DSE 210)

    Resources

    Stars

    Watchers

    Forks

    Releases

    No releases published

    Packages

    No packages published