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Mounika Janapati MOUNIKA-EXPERTSHUB

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MOUNIKA-EXPERTSHUB / links.csv
Created November 26, 2019 16:06
Created on Cognitive Class Labs
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MOUNIKA-EXPERTSHUB / ML0101EN-Clus-DBSCN-weather-py-v1.ipynb
Created November 26, 2019 15:23
Created on Cognitive Class Labs
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MOUNIKA-EXPERTSHUB / weather-stations20140101-20141231.csv
Created November 26, 2019 15:22
Created on Cognitive Class Labs
Stn_Name Lat Long Prov Tm DwTm D Tx DwTx Tn DwTn S DwS S%N P DwP P%N S_G Pd BS DwBS BS% HDD CDD Stn_No
CHEMAINUS 48.935 -123.742 BC 8.2 0 NA 13.5 0 1 0 0 0 NA 178.8 0 NA 0 12 NA 273.3 0 1011500
COWICHAN LAKE FORESTRY 48.824 -124.133 BC 7 0 3 15 0 -3 0 0 0 0 258.6 0 104 0 12 NA 307 0 1012040
LAKE COWICHAN 48.829 -124.052 BC 6.8 13 2.8 16 9 -2.5 9 0 9 NA 264.6 9 NA 11 NA 168.1 0 1012055
DISCOVERY ISLAND 48.425 -123.226 BC NA 12.5 0 NA NA NA 1012475
DUNCAN KELVIN CREEK 48.735 -123.728 BC 7.7 2 3.4 14.5 2 -1 2 0 2 NA 168.4 2 NA 11 NA 267.7 0 1012573
ESQUIMALT HARBOUR 48.432 -123.439 BC 8.8 0 NA 13.1 0 1.9 0 NA 81 8 NA 12 NA 258.6 0 1012710
GALIANO NORTH 48.985 -123.573 BC 8.9 7 NA 13.5 7 2 7 0 7 NA 110 7 NA 0 10 NA 191.7 0 10130MN
MALAHAT 48.575 -123.53 BC 7.2 1 NA 12.7 1 2.2 0 NA 108.8 10 NA 12 NA 290.8 0 1014820
METCHOSIN 48.374 -123.561 BC NA 0 0 0 102.6 0 95 0 16 NA 1015105
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MOUNIKA-EXPERTSHUB / cars_clus.csv
Created November 26, 2019 11:18
Created on Cognitive Class Labs
We can make this file beautiful and searchable if this error is corrected: It looks like row 10 should actually have 16 columns, instead of 11 in line 9.
manufact,model,sales,resale,type,price,engine_s,horsepow,wheelbas,width,length,curb_wgt,fuel_cap,mpg,lnsales,partition
Acura,Integra,16.919,16.360,0.000,21.500,1.800,140.000,101.200,67.300,172.400,2.639,13.200,28.000,2.828,0.000
Acura,TL,39.384,19.875,0.000,28.400,3.200,225.000,108.100,70.300,192.900,3.517,17.200,25.000,3.673,0.000
Acura,CL,14.114,18.225,0.000,$null$,3.200,225.000,106.900,70.600,192.000,3.470,17.200,26.000,2.647,0.000
Acura,RL,8.588,29.725,0.000,42.000,3.500,210.000,114.600,71.400,196.600,3.850,18.000,22.000,2.150,0.000
Audi,A4,20.397,22.255,0.000,23.990,1.800,150.000,102.600,68.200,178.000,2.998,16.400,27.000,3.015,0.000
Audi,A6,18.780,23.555,0.000,33.950,2.800,200.000,108.700,76.100,192.000,3.561,18.500,22.000,2.933,0.000
Audi,A8,1.380,39.000,0.000,62.000,4.200,310.000,113.000,74.000,198.200,3.902,23.700,21.000,0.322,0.000
BMW,323i,19.747,$null$,0.000,26.990,2.500,170.000,107.300,68.400,176.000,3.179,16.600,26.100,2.983,0.000
BMW,328i,9.231,28.675,0.000,33.400,2.800,193.000,107.300,68.500,1
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MOUNIKA-EXPERTSHUB / cell_samples.csv
Created November 26, 2019 07:20
Created on Cognitive Class Labs
ID Clump UnifSize UnifShape MargAdh SingEpiSize BareNuc BlandChrom NormNucl Mit Class
1000025 5 1 1 1 2 1 3 1 1 2
1002945 5 4 4 5 7 10 3 2 1 2
1015425 3 1 1 1 2 2 3 1 1 2
1016277 6 8 8 1 3 4 3 7 1 2
1017023 4 1 1 3 2 1 3 1 1 2
1017122 8 10 10 8 7 10 9 7 1 4
1018099 1 1 1 1 2 10 3 1 1 2
1018561 2 1 2 1 2 1 3 1 1 2
1033078 2 1 1 1 2 1 1 1 5 2
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MOUNIKA-EXPERTSHUB / ML0101EN-Clas-SVM-cancer-py-v1.ipynb
Created November 26, 2019 07:19
Created on Cognitive Class Labs
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MOUNIKA-EXPERTSHUB / ChurnData.csv
Created November 26, 2019 05:42
Created on Cognitive Class Labs
We can make this file beautiful and searchable if this error is corrected: It looks like row 6 should actually have 28 columns, instead of 17 in line 5.
tenure,age,address,income,ed,employ,equip,callcard,wireless,longmon,tollmon,equipmon,cardmon,wiremon,longten,tollten,cardten,voice,pager,internet,callwait,confer,ebill,loglong,logtoll,lninc,custcat,churn
11.000,33.000,7.000,136.000,5.000,5.000,0.000,1.000,1.000,4.400,20.750,0.000,15.250,35.700,42.000,211.450,125.000,1.000,1.000,0.000,1.000,1.000,0.000,1.482,3.033,4.913,4.000,1.000
33.000,33.000,12.000,33.000,2.000,0.000,0.000,0.000,0.000,9.450,0.000,0.000,0.000,0.000,288.800,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,2.246,3.240,3.497,1.000,1.000
23.000,30.000,9.000,30.000,1.000,2.000,0.000,0.000,0.000,6.300,0.000,0.000,0.000,0.000,157.050,0.000,0.000,0.000,0.000,0.000,0.000,1.000,0.000,1.841,3.240,3.401,3.000,0.000
38.000,35.000,5.000,76.000,2.000,10.000,1.000,1.000,1.000,6.050,45.000,50.100,23.250,64.900,239.550,1873.050,880.000,1.000,1.000,1.000,1.000,1.000,1.000,1.800,3.807,4.331,4.000,0.000
7.000,35.000,14.000,80.000,2.000,15.000,0.000,1.000,0.000,7.100,22.000,0.000,23.750,0.000,47.450,166.100,145.0
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