More detailed instructions deep learning

Solved!
Perazen73
Level 2
More detailed instructions deep learning
Are there any alternative online courses than the 'first deep learning model' on the dataiku academy?

I find the existing tutorial https://academy.dataiku.com/latest/tutorial/machine-learning/deep-learning-first.html confusing. Probably it is just my impatience and lack of specific knowledge.

e.g. the mandatory installation of Keras, TensorFlow packages into DSS. There is indeed a link to Keras.io with instructions how to install this in Python, but how do I install this package in DSS? By the time I find out myself I have lost another valuable hour where instead I would like to focus on the modelling in DSS.

I really hope there are some additional or alternative online courses or tutorials that can guide me through this step by step.
0 Kudos
1 Solution
AdrienL
Dataiker

Hi,



The procedure to install it is in the page you linked:



You will need access to a code environment with the necessary libraries. When creating a code environment, you can add sets of packages on the Packages to Install tab. Choose the Visual Deep Learning package set that corresponds to the hardware youโ€™re running on.



You need to create a code environement, and then add the "Visual Deep Learning" packages to it. This will add the required packages, including keras and tensorflow.

View solution in original post

2 Replies
AdrienL
Dataiker

Hi,



The procedure to install it is in the page you linked:



You will need access to a code environment with the necessary libraries. When creating a code environment, you can add sets of packages on the Packages to Install tab. Choose the Visual Deep Learning package set that corresponds to the hardware youโ€™re running on.



You need to create a code environement, and then add the "Visual Deep Learning" packages to it. This will add the required packages, including keras and tensorflow.

Perazen73
Level 2
Author
Thanks Adrien,

I found that knowing the correct sequence of steps and also knowing where to click in DSS 6 makes a big difference in setting this up quickly. This an overview of the steps I took (based on the tutorial) just in case someone else struggles with it.

STEP 1 - create a code environment (e.g. Python)
https://doc.dataiku.com/dss/latest/code-envs/operations-python.html#create-a-code-environment
* access this menu on the DSS home page by clicking the 'apps' icon (9 dots) in the right top corner to see the dropdown list
*select 'administration' option at the bottom of the list
*At the right top corner now select 'Code Envs'
*select 'NEW PYTHON ENV'
*provide a name for the environment e.g. 'python36-code-env' (note DSS states version 3.x are experimental)
*change the Python version to your preference. In this case 'Python 3.6 (from PATH)
*click 'Create' at the right bottom of the popup window. (this will take a minute to complete)
*click on the code env name you just created to open it
*at the left select 'Packages to install'
*at the right bottom of the page select 'ADD SETS OF PACKAGES' (or visual machine learning and deep learning)
* in the popup window select all the codes (control + right click) and click 'ADD'
*at the left select 'SAVE AND UPDATE'
*at the right bottom of the page select 'ADD SETS OF PACKAGES' a 2nd time
* repeat the process of adding packages for โ€˜Visual deep learning: Keras, Tensorflow (CPU)โ€™ in the required packages drop-down list that you have not yet selected in the previous run. If you select the same package e.g. โ€˜scipy>=1.1,<1.2โ€™ for both 'visual machine learningโ€™ and for โ€˜visual deep learningโ€™ the package installer will return an error.

STEP 2 โ€“ Access a code environment (per project)
https://academy.dataiku.com/latest/tutorial/code/code-env.html
* Click on a project
* click on the 3 dots icon on the top menu bar (top left of the page)
* in the drop-down list select โ€˜settingsโ€™ (this will bring you to the โ€˜project settingsโ€™ page
* in the left menu click on โ€˜Code env selectionโ€™
* untick the โ€˜Use DSS builtin Python envโ€™ tick box
* select the environment drop-down list to select the added Python environment
*save the setting

Labels

?
Labels (2)
A banner prompting to get Dataiku