Комментарии:
Great. So this works on Linux, not Windows.
ОтветитьAmazing session!!❤
ОтветитьThanks a lot for the clear explanation
ОтветитьVery helpful introduction.
Thank you.
Hi Aman, are you planning to make part 2 of this video ?
ОтветитьThank you for this amazing video! for those still having the "airflow.exceptions.AirflowException: `python_callable` param must be callable" error despite removing the parenthesis you have to rename the function to something else too, like print_world_func. I was still having this error because the name of the callable function was the same name as the PythonOperator here " PRINT_WORLD = PythonOperator(task_id='print_world',
python_callable=PRINT_WORLD)
Thanks for the tutorial !
ОтветитьNice explanation 👍
ОтветитьGreat and simple
ОтветитьExactly what I wanted. Thank you for great video.
Ответитьvery good explanation Aman is this course available in your website?
Ответитьvery helpful tutorial , Please make tutorial on spark and kafka
Ответитьamazing course ... Aman please add courses for deployment and monitoring framework with use case. Especially how stakeholders can access the predictions with api. As always you are super helpful
ОтветитьBest Tutorial.please can you make more video on airflow?
ОтветитьVery helpful and easy to understand ❤
Ответитьbro make more videos on ML and DL and cloud technologies for students
Ответитьyou are our saviour aman ..thank u very much
ОтветитьGreat Tutorial.
Kubernetes and Kubeflow series would also be a great addon