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.ipynb_checkpoints
.ipynb_checkpoints
 
 
1.tsv
1.tsv
 
 
1NN vs RandomForest.ipynb
1NN vs RandomForest.ipynb
 
 
Bike Sharing Demand - sklearn_part1.ipynb
Bike Sharing Demand - sklearn_part1.ipynb
 
 
Bike Sharing Demand - sklearn_part2.ipynb
Bike Sharing Demand - sklearn_part2.ipynb
 
 
Confident intervals based on bootstrap.ipynb
Confident intervals based on bootstrap.ipynb
 
 
Confident intervals for 2 proportion.ipynb
Confident intervals for 2 proportion.ipynb
 
 
Confident intervals for mean.ipynb
Confident intervals for mean.ipynb
 
 
Confident intervals for proportion.ipynb
Confident intervals for proportion.ipynb
 
 
Functional_programming.ipynb
Functional_programming.ipynb
 
 
Hypothesis test Binom.ipynb
Hypothesis test Binom.ipynb
 
 
Hypothesis test Chi-square.ipynb
Hypothesis test Chi-square.ipynb
 
 
NumPy_-SciPy_-Matplotlib-intro.ipynb
NumPy_-SciPy_-Matplotlib-intro.ipynb
 
 
README.md
README.md
 
 
SciPy-Optimization.ipynb
SciPy-Optimization.ipynb
 
 
banner_click_stat.txt
banner_click_stat.txt
 
 
beauty.csv
beauty.csv
 
 
bike_sharing_demand.csv
bike_sharing_demand.csv
 
 
bioresponse.csv
bioresponse.csv
 
 
data_reading.ipynb
data_reading.ipynb
 
 
data_writing.ipynb
data_writing.ipynb
 
 
dataset.tsv
dataset.tsv
 
 
example_koi_8.txt
example_koi_8.txt
 
 
example_utf8.txt
example_utf8.txt
 
 
fertility.txt
fertility.txt
 
 
foodmart.products.tsv
foodmart.products.tsv
 
 
foodmart.sales.tsv
foodmart.sales.tsv
 
 
matrix_operations-.ipynb
matrix_operations-.ipynb
 
 
mirror_mouses.txt
mirror_mouses.txt
 
 
pandas_dataframe.ipynb
pandas_dataframe.ipynb
 
 
sample_distribution_evaluation.ipynb
sample_distribution_evaluation.ipynb
 
 
seattle.txt
seattle.txt
 
 
sklearn.cross_validation.ipynb
sklearn.cross_validation.ipynb
 
 
sklearn.datasets.ipynb
sklearn.datasets.ipynb
 
 
sklearn.decision_trees.ipynb
sklearn.decision_trees.ipynb
 
 
sklearn.grid_search.ipynb
sklearn.grid_search.ipynb
 
 
sklearn.linear_model_part1.ipynb
sklearn.linear_model_part1.ipynb
 
 
sklearn.linear_model_part2.ipynb
sklearn.linear_model_part2.ipynb
 
 
sklearn.random_forest.ipynb
sklearn.random_forest.ipynb
 
 
sklearn.rf_vs_gb.ipynb
sklearn.rf_vs_gb.ipynb
 
 
stat.correlation.ipynb
stat.correlation.ipynb
 
 
stat.multiple_hypothesis_testing.ipynb
stat.multiple_hypothesis_testing.ipynb
 
 
stat.non_parametric_tests_1sample.ipynb
stat.non_parametric_tests_1sample.ipynb
 
 
stat.non_parametric_tests_ind.ipynb
stat.non_parametric_tests_ind.ipynb
 
 
stat.non_parametric_tests_rel.ipynb
stat.non_parametric_tests_rel.ipynb
 
 
stat.regression.ipynb
stat.regression.ipynb
 
 
stochastic_variables.ipynb
stochastic_variables.ipynb
 
 
updated_dataset.csv
updated_dataset.csv
 
 
vector_operations.ipynb
vector_operations.ipynb
 
 
verizon.txt
verizon.txt
 
 
weight.txt
weight.txt
 
 
Прогнозирование временных рядов.ipynb
Прогнозирование временных рядов.ipynb
 
 

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DA_and_ML_Python_Basics

Here I'm collecting basic Python for machine learning (ML) and data analysis (DA).

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