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)