ML, conda, feature enginering.md

for install apache-beam

• conda create -n py27 python=2.7 ipykernel
• conda activate py27

p=beam.Pipeline();
(p
|'Create' >> beam.io.ReadFromText("some.txt",'a')
#|'Create' >> beam.Create(["1", "2", "3"])
|'func'>> beam.FlatMap(lambda q: myFunc(q))
|'Out' >> beam.io.WriteToText("res0.txt",'a')
)
p.run()

y = tf.nn.softmax(tf.matmul(x,W) + b)
Just pull on node y and you'll have what you want.

feed_dict = {x: [your_image]}
classification = tf.run(y, feed_dict)
print classification

чтоб дата быстрее парсилась
ir=pd.read_csv(path,nrows=nrows,date_parser=lambda x:datetime.datetime.strptime(x,'%Y-%m-%d %H:%M:%S %Z'))