RayWu raywu60kg

## python-dockerfile
FROM python:3.6.9-slim-buster as base
WORKDIR /usr/src/app
ADD Pipfile .
ADD Pipfile.lock .
ADD jupyter_notebook_config.py /root/.jupyter/jupyter_notebook_config.py
RUN apt-get update -qq && \
    apt-get install -yqq apt-utils && \
    apt-get install -yqq procps && \
    apt-get install -yqq gcc &&\
    apt-get install -yqq cron &&\

## makefile
TAG="jupyter/jupyter:dev"
build:
  docker build -f Dockerfile -t ${TAG} .
run-jupyter:
  docker run --rm -it -v $(shell pwd):/usr/src/app -p 8888:8888 -d $(TAG) "jupyter notebook --ip=0.0.0.0 --port=8888 --allow-root"

## jupyter_notebook_config.py
# Configuration file for jupyter-notebook.

#------------------------------------------------------------------------------
# Application(SingletonConfigurable) configuration
#------------------------------------------------------------------------------

## This is an application.

## The date format used by logging formatters for %(asctime)s
#c.Application.log_datefmt = '%Y-%m-%d %H:%M:%S'

## query.sql
CREATE TABLE KidWts (Name nvarchar(20),Age int ,Weight float);
INSERT INTO KidWts VALUES
(‘Lily’,3,15)
, (‘Muhammad’,30,98)
, (‘Daphne’, 3, 16)
, (‘Max’, 2, 12)
,(‘Chloe’,1,11)
,(‘Jackie’,2,14)
,(‘Albert’,3,17)
;

## big-iris.csv

          
            sepal.length
            sepal.width
            petal.length
            petal.width
            variety

            
              5.1
              3.5
              1.4
              .2
              Setosa

            
              4.9
              3
              1.4
              .2
              Setosa

            
              4.7
              3.2
              1.3
              .2
              Setosa

            
              4.6
              3.1
              1.5
              .2
              Setosa

            
              5
              3.6
              1.4
              .2
              Setosa

            
              5.4
              3.9
              1.7
              .4
              Setosa

            
              4.6
              3.4
              1.4
              .3
              Setosa

            
              5
              3.4
              1.5
              .2
              Setosa

            
              4.4
              2.9
              1.4
              .2
              Setosa

## keras_def_model.py
# def model
inputs = {}
for feature_name in (feature_list):

    inputs[feature_name] = tf.keras.Input(shape=(1), name=feature_name)

label = tf.keras.layers.Dense(
    1, activation='sigmoid', name='label')(x)
model = tf.keras.Model(inputs=inputs, outputs=label)
model.compile(
	FROM python:3.6.9-slim-buster as base
	WORKDIR /usr/src/app
	ADD Pipfile .
	ADD Pipfile.lock .
	ADD jupyter_notebook_config.py /root/.jupyter/jupyter_notebook_config.py
	RUN apt-get update -qq && \
	apt-get install -yqq apt-utils && \
	apt-get install -yqq procps && \
	apt-get install -yqq gcc &&\
	apt-get install -yqq cron &&\
	TAG="jupyter/jupyter:dev"
	build:
	docker build -f Dockerfile -t ${TAG} .
	run-jupyter:
	docker run --rm -it -v $(shell pwd):/usr/src/app -p 8888:8888 -d $(TAG) "jupyter notebook --ip=0.0.0.0 --port=8888 --allow-root"
	# Configuration file for jupyter-notebook.

	#------------------------------------------------------------------------------
	# Application(SingletonConfigurable) configuration
	#------------------------------------------------------------------------------

	## This is an application.

	## The date format used by logging formatters for %(asctime)s
	#c.Application.log_datefmt = '%Y-%m-%d %H:%M:%S'
	CREATE TABLE KidWts (Name nvarchar(20),Age int ,Weight float);
	INSERT INTO KidWts VALUES
	(‘Lily’,3,15)
	, (‘Muhammad’,30,98)
	, (‘Daphne’, 3, 16)
	, (‘Max’, 2, 12)
	,(‘Chloe’,1,11)
	,(‘Jackie’,2,14)
	,(‘Albert’,3,17)
	;
sepal.length	sepal.width	petal.length	petal.width	variety
5.1	3.5	1.4	.2	Setosa
4.9	3	1.4	.2	Setosa
4.7	3.2	1.3	.2	Setosa
4.6	3.1	1.5	.2	Setosa
5	3.6	1.4	.2	Setosa
5.4	3.9	1.7	.4	Setosa
4.6	3.4	1.4	.3	Setosa
5	3.4	1.5	.2	Setosa
4.4	2.9	1.4	.2	Setosa
	# def model
	inputs = {}
	for feature_name in (feature_list):

	inputs[feature_name] = tf.keras.Input(shape=(1), name=feature_name)

	label = tf.keras.layers.Dense(
	1, activation='sigmoid', name='label')(x)
	model = tf.keras.Model(inputs=inputs, outputs=label)
	model.compile(