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README.md
README.md
 
 
aws.js
aws.js
 
 
data.p
data.p
 
 
dataclean_ws.py
dataclean_ws.py
 
 
dataclean_ws2.py
dataclean_ws2.py
 
 
dataclean_ws_test.py
dataclean_ws_test.py
 
 
datacleaning.py
datacleaning.py
 
 
fixed.csv
fixed.csv
 
 
forWeka.csv
forWeka.csv
 
 
forWeka2.csv
forWeka2.csv
 
 
genres.py
genres.py
 
 
get.js
get.js
 
 
helper.py
helper.py
 
 
imbdpython.py
imbdpython.py
 
 
join.py
join.py
 
 
joined.csv
joined.csv
 
 
joined_100.csv
joined_100.csv
 
 
joined_25.csv
joined_25.csv
 
 
new_out.csv
new_out.csv
 
 
new_out2.csv
new_out2.csv
 
 
new_out_test.csv
new_out_test.csv
 
 
new_out_with_finance.csv
new_out_with_finance.csv
 
 
new_out_with_finance_12.csv
new_out_with_finance_12.csv
 
 
new_out_with_finance_3.csv
new_out_with_finance_3.csv
 
 
new_out_with_finance_for_weka.csv
new_out_with_finance_for_weka.csv
 
 
new_out_with_finance_range_0_200000.csv
new_out_with_finance_range_0_200000.csv
 
 
new_out_with_finance_range_1000000_1200000.csv
new_out_with_finance_range_1000000_1200000.csv
 
 
new_out_with_finance_range_1200000_1400000.csv
new_out_with_finance_range_1200000_1400000.csv
 
 
new_out_with_finance_range_1400000_1600000.csv
new_out_with_finance_range_1400000_1600000.csv
 
 
new_out_with_finance_range_1600000_1800000.csv
new_out_with_finance_range_1600000_1800000.csv
 
 
new_out_with_finance_range_1800000_2000000.csv
new_out_with_finance_range_1800000_2000000.csv
 
 
new_out_with_finance_range_2000000_2500000.csv
new_out_with_finance_range_2000000_2500000.csv
 
 
new_out_with_finance_range_200000_400000.csv
new_out_with_finance_range_200000_400000.csv
 
 
new_out_with_finance_range_2000_20000.csv
new_out_with_finance_range_2000_20000.csv
 
 
new_out_with_finance_range_2500000_3000000.csv
new_out_with_finance_range_2500000_3000000.csv
 
 
new_out_with_finance_range_2500000_3000000_2.csv
new_out_with_finance_range_2500000_3000000_2.csv
 
 
new_out_with_finance_range_3000000_3200000.csv
new_out_with_finance_range_3000000_3200000.csv
 
 
new_out_with_finance_range_3000000_3200000_2.csv
new_out_with_finance_range_3000000_3200000_2.csv
 
 
new_out_with_finance_range_3200000_3500000.csv
new_out_with_finance_range_3200000_3500000.csv
 
 
new_out_with_finance_range_3500000_4000000.csv
new_out_with_finance_range_3500000_4000000.csv
 
 
new_out_with_finance_range_4000000_4587532.csv
new_out_with_finance_range_4000000_4587532.csv
 
 
new_out_with_finance_range_4000000_4587532_2.csv
new_out_with_finance_range_4000000_4587532_2.csv
 
 
new_out_with_finance_range_400000_700000.csv
new_out_with_finance_range_400000_700000.csv
 
 
new_out_with_finance_range_500_800.csv
new_out_with_finance_range_500_800.csv
 
 
new_out_with_finance_range_700000_1000000.csv
new_out_with_finance_range_700000_1000000.csv
 
 
new_out_with_finance_range_800_2000.csv
new_out_with_finance_range_800_2000.csv
 
 
nn.py
nn.py
 
 
nn2.py
nn2.py
 
 
nn3.py
nn3.py
 
 
nn3_withexp.py
nn3_withexp.py
 
 
nn4.py
nn4.py
 
 
nn5.py
nn5.py
 
 
nn6.py
nn6.py
 
 
nn6_1.py
nn6_1.py
 
 
nnFINAL.py
nnFINAL.py
 
 
nnweights.p
nnweights.p
 
 
title.ratings.tsv.gz
title.ratings.tsv.gz
 
 
webscrap.py
webscrap.py
 
 

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Opening_Weekend

Given data from IMDB that includes a range of features as well as numbers on opening weekends, build a model that predicts opening weekends and then modifies its model in response to new data.

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Given data from IMDB that includes a range of features as well as numbers on opening weekends, build a model that predicts opening weekends and then modifies its model in response to new data.

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