Olar Alex qbeer

## create_tf_records_from_images.py
# Tensorflow throws a bunch of `FutureWarning`s
import warnings
warnings.simplefilter(action='ignore', category=FutureWarning)

import tensorflow as tf
import glob

BUFFER_SIZE = 50000
BATCH_SIZE = 32
IMAGE_HEIGHT = 64

## titanic.csv

          
            PassengerId
            Survived
            Pclass
            Name
            Sex
            Age
            SibSp
            Parch
            Ticket
            Fare
            Cabin
            Embarked

            
              1
              0
              3
              Braund, Mr. Owen Harris
              male
              22
              1
              0
              A/5 21171
              7.25
              
              S

            
              2
              1
              1
              Cumings, Mrs. John Bradley (Florence Briggs Thayer)
              female
              38
              1
              0
              PC 17599
              71.2833
              C85
              C

            
              3
              1
              3
              Heikkinen, Miss. Laina
              female
              26
              0
              0
              STON/O2. 3101282
              7.925
              
              S

            
              4
              1
              1
              Futrelle, Mrs. Jacques Heath (Lily May Peel)
              female
              35
              1
              0
              113803
              53.1
              C123
              S

            
              5
              0
              3
              Allen, Mr. William Henry
              male
              35
              0
              0
              373450
              8.05
              
              S

            
              6
              0
              3
              Moran, Mr. James
              male
              
              0
              0
              330877
              8.4583
              
              Q

            
              7
              0
              1
              McCarthy, Mr. Timothy J
              male
              54
              0
              0
              17463
              51.8625
              E46
              S

            
              8
              0
              3
              Palsson, Master. Gosta Leonard
              male
              2
              3
              1
              349909
              21.075
              
              S

            
              9
              1
              3
              Johnson, Mrs. Oscar W (Elisabeth Vilhelmina Berg)
              female
              27
              0
              2
              347742
              11.1333
              
              S

## hw1.ipynb

      
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                HW1.ipynb
              
          
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## HW_02.ipynb

      
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                02_BLANK.ipynb
              
          
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## 02_dataset_worldbank_jobs_2016.tsv
Country Name	Country Code	Series Name	Series Code	2016 [YR2016]
Afghanistan	AFG	Access to electricity (% of population)	EG.ELC.ACCS.ZS	84.1371383666992
Afghanistan	AFG	Adolescent fertility rate (births per 1,000 women ages 15-19)	SP.ADO.TFRT	68.7942
Afghanistan	AFG	Age dependency ratio (% of working-age population)	SP.POP.DPND	86.5709321507136
Afghanistan	AFG	Agriculture, value added (% of GDP)	NV.AGR.TOTL.ZS	20.9658976104561
Afghanistan	AFG	Agriculture, value added (annual % growth)	NV.AGR.TOTL.KD.ZG	5.97175068925613
Afghanistan	AFG	Agriculture, value added (constant 2005 US$)	NV.AGR.TOTL.KD	4535103188.06536
Afghanistan	AFG	Air transport, registered carrier departures worldwide	IS.AIR.DPRT	22770
Afghanistan	AFG	Automated teller machines (ATMs) (per 100,000 adults)	FB.ATM.TOTL.P5	1.07421538203442
Afghanistan	AFG	Borrowers from commercial banks (per 1,000 adults)	FB.CBK.BRWR.P3	3.05195383587665

## 01_solved_eda.ipynb

      
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                01_SOLVED_EDA.ipynb
              
          
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## lab03.ipynb

      
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              September 20, 2021 14:47
            
              
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## winequality-red.csv
"fixed acidity";"volatile acidity";"citric acid";"residual sugar";"chlorides";"free sulfur dioxide";"total sulfur dioxide";"density";"pH";"sulphates";"alcohol";"quality"
7.4;0.7;0;1.9;0.076;11;34;0.9978;3.51;0.56;9.4;5
7.8;0.88;0;2.6;0.098;25;67;0.9968;3.2;0.68;9.8;5
7.8;0.76;0.04;2.3;0.092;15;54;0.997;3.26;0.65;9.8;5
11.2;0.28;0.56;1.9;0.075;17;60;0.998;3.16;0.58;9.8;6
7.4;0.7;0;1.9;0.076;11;34;0.9978;3.51;0.56;9.4;5
7.4;0.66;0;1.8;0.075;13;40;0.9978;3.51;0.56;9.4;5
7.9;0.6;0.06;1.6;0.069;15;59;0.9964;3.3;0.46;9.4;5
7.3;0.65;0;1.2;0.065;15;21;0.9946;3.39;0.47;10;7
7.8;0.58;0.02;2;0.073;9;18;0.9968;3.36;0.57;9.5;7

## HW_2_solved.ipynb

      
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## real_estate.csv

          
            No
            X1 transaction date
            X2 house age
            X3 distance to the nearest MRT station
            X4 number of convenience stores
            X5 latitude
            X6 longitude
            Y house price of unit area

            
              1
              2012.917
              32
              84.87882
              10
              24.98298
              121.54024
              37.9

            
              2
              2012.917
              19.5
              306.5947
              9
              24.98034
              121.53951
              42.2

            
              3
              2013.583
              13.3
              561.9845
              5
              24.98746
              121.54391
              47.3

            
              4
              2013.500
              13.3
              561.9845
              5
              24.98746
              121.54391
              54.8

            
              5
              2012.833
              5
              390.5684
              5
              24.97937
              121.54245
              43.1

            
              6
              2012.667
              7.1
              2175.03
              3
              24.96305
              121.51254
              32.1

            
              7
              2012.667
              34.5
              623.4731
              7
              24.97933
              121.53642
              40.3

            
              8
              2013.417
              20.3
              287.6025
              6
              24.98042
              121.54228
              46.7

            
              9
              2013.500
              31.7
              5512.038
              1
              24.95095
              121.48458
              18.8
	# Tensorflow throws a bunch of `FutureWarning`s
	import warnings
	warnings.simplefilter(action='ignore', category=FutureWarning)

	import tensorflow as tf
	import glob

	BUFFER_SIZE = 50000
	BATCH_SIZE = 32
	IMAGE_HEIGHT = 64
PassengerId	Survived	Pclass	Name	Sex	Age	SibSp	Parch	Ticket	Fare	Cabin	Embarked
1	0	3	Braund, Mr. Owen Harris	male	22	1	0	A/5 21171	7.25		S
2	1	1	Cumings, Mrs. John Bradley (Florence Briggs Thayer)	female	38	1	0	PC 17599	71.2833	C85	C
3	1	3	Heikkinen, Miss. Laina	female	26	0	0	STON/O2. 3101282	7.925		S
4	1	1	Futrelle, Mrs. Jacques Heath (Lily May Peel)	female	35	1	0	113803	53.1	C123	S
5	0	3	Allen, Mr. William Henry	male	35	0	0	373450	8.05		S
6	0	3	Moran, Mr. James	male		0	0	330877	8.4583		Q
7	0	1	McCarthy, Mr. Timothy J	male	54	0	0	17463	51.8625	E46	S
8	0	3	Palsson, Master. Gosta Leonard	male	2	3	1	349909	21.075		S
9	1	3	Johnson, Mrs. Oscar W (Elisabeth Vilhelmina Berg)	female	27	0	2	347742	11.1333		S
	Country Name Country Code Series Name Series Code 2016 [YR2016]
	Afghanistan AFG Access to electricity (% of population) EG.ELC.ACCS.ZS 84.1371383666992
	Afghanistan AFG Adolescent fertility rate (births per 1,000 women ages 15-19) SP.ADO.TFRT 68.7942
	Afghanistan AFG Age dependency ratio (% of working-age population) SP.POP.DPND 86.5709321507136
	Afghanistan AFG Agriculture, value added (% of GDP) NV.AGR.TOTL.ZS 20.9658976104561
	Afghanistan AFG Agriculture, value added (annual % growth) NV.AGR.TOTL.KD.ZG 5.97175068925613
	Afghanistan AFG Agriculture, value added (constant 2005 US$) NV.AGR.TOTL.KD 4535103188.06536
	Afghanistan AFG Air transport, registered carrier departures worldwide IS.AIR.DPRT 22770
	Afghanistan AFG Automated teller machines (ATMs) (per 100,000 adults) FB.ATM.TOTL.P5 1.07421538203442
	Afghanistan AFG Borrowers from commercial banks (per 1,000 adults) FB.CBK.BRWR.P3 3.05195383587665
	"fixed acidity";"volatile acidity";"citric acid";"residual sugar";"chlorides";"free sulfur dioxide";"total sulfur dioxide";"density";"pH";"sulphates";"alcohol";"quality"
	7.4;0.7;0;1.9;0.076;11;34;0.9978;3.51;0.56;9.4;5
	7.8;0.88;0;2.6;0.098;25;67;0.9968;3.2;0.68;9.8;5
	7.8;0.76;0.04;2.3;0.092;15;54;0.997;3.26;0.65;9.8;5
	11.2;0.28;0.56;1.9;0.075;17;60;0.998;3.16;0.58;9.8;6
	7.4;0.7;0;1.9;0.076;11;34;0.9978;3.51;0.56;9.4;5
	7.4;0.66;0;1.8;0.075;13;40;0.9978;3.51;0.56;9.4;5
	7.9;0.6;0.06;1.6;0.069;15;59;0.9964;3.3;0.46;9.4;5
	7.3;0.65;0;1.2;0.065;15;21;0.9946;3.39;0.47;10;7
	7.8;0.58;0.02;2;0.073;9;18;0.9968;3.36;0.57;9.5;7
No	X1 transaction date	X2 house age	X3 distance to the nearest MRT station	X4 number of convenience stores	X5 latitude	X6 longitude	Y house price of unit area
1	2012.917	32	84.87882	10	24.98298	121.54024	37.9
2	2012.917	19.5	306.5947	9	24.98034	121.53951	42.2
3	2013.583	13.3	561.9845	5	24.98746	121.54391	47.3
4	2013.500	13.3	561.9845	5	24.98746	121.54391	54.8
5	2012.833	5	390.5684	5	24.97937	121.54245	43.1
6	2012.667	7.1	2175.03	3	24.96305	121.51254	32.1
7	2012.667	34.5	623.4731	7	24.97933	121.53642	40.3
8	2013.417	20.3	287.6025	6	24.98042	121.54228	46.7
9	2013.500	31.7	5512.038	1	24.95095	121.48458	18.8