Susan Li susanli2016

## Bay_Area_Bike Share_Analysis.ipynb

      
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              December 3, 2016 00:13
            
              
                Bay Area Bike Share Analysis
              
          
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## Toronto-Weather.ipynb

      
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                susanli2016
                / Toronto-Weather.ipynb
            
            
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              December 9, 2016 07:03
            
              
                Toronto Weather
              
          
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## Vancouver_Auto_Crime.ipynb

      
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                / Vancouver_Auto_Crime.ipynb
            
            
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              December 9, 2016 07:40
            
              
                Auto Crime in Vancouver
              
          
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## Baby_names_alberta.ipynb

      
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              December 14, 2016 07:43
            
              
                Baby Names in Alberta
              
          
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## Referee_data.ipynb

      
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              December 24, 2016 18:38
            
              
                Referee Data
              
          
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## Immigration_to_us.ipynb

      
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                susanli2016
                / Immigration_to_us.ipynb
            
            
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              December 29, 2016 09:06
            
              
                33 Years of U.S. Immigration
              
          
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## Edmonton_crime.ipynb

      
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              December 29, 2016 09:51
            
              
                Edmonton Crime Data Analysis
              
          
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## OpenStreetMap.ipynb

      
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                / OpenStreetMap.ipynb
            
            
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              February 9, 2017 10:19
            
              
                Wrangle OpenStreetMap Data
              
          
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## svm
from sklearn.linear_model import SGDClassifier

sgd = Pipeline([('vect', CountVectorizer()),
                ('tfidf', TfidfTransformer()),
                ('clf', SGDClassifier(loss='hinge', penalty='l2',alpha=1e-3, random_state=42, max_iter=5, tol=None)),
               ])
sgd.fit(X_train, y_train)

%%time

## logreg
from sklearn.linear_model import LogisticRegression

logreg = Pipeline([('vect', CountVectorizer()),
                ('tfidf', TfidfTransformer()),
                ('clf', LogisticRegression(n_jobs=1, C=1e5)),
               ])
logreg.fit(X_train, y_train)

%%time
	from sklearn.linear_model import SGDClassifier

	sgd = Pipeline([('vect', CountVectorizer()),
	('tfidf', TfidfTransformer()),
	('clf', SGDClassifier(loss='hinge', penalty='l2',alpha=1e-3, random_state=42, max_iter=5, tol=None)),
	])
	sgd.fit(X_train, y_train)

	%%time
	from sklearn.linear_model import LogisticRegression

	logreg = Pipeline([('vect', CountVectorizer()),
	('tfidf', TfidfTransformer()),
	('clf', LogisticRegression(n_jobs=1, C=1e5)),
	])
	logreg.fit(X_train, y_train)

	%%time