Machine learning development hub
The described technology is generally directed towards a machine learning development hub, and corresponding methods and computer readable media. The machine learning development hub can comprise a machine learning development platform complete with various tools for various stages of machine learning development. The machine learning development hub can furthermore comprise translation functions to translate received inputs into inputs to other machine learning development platforms. The machine learning development hub can collect credentials for the other machine learning development platforms and can connect to the other machine learning development platforms via their respective interfaces, in order to supply inputs and instructions thereto. The machine learning development hub can encrypt its communications to other machine learning development platforms to secure its interactions.
1. A method, comprising:
provisioning, by a server comprising a processor, a workspace comprising:
a first user interface for a first machine learning development platform that employs a first type of machine learning development tool for generating machine learning models, and
a second user interface for a second machine learning development platform that employs a second type of machine learning development tool that is different from the first type of machine learning development tool for generating machine learning models, wherein the first machine learning development platform is distinct from the second machine learning development platform;
obtaining, by the server, a user credential to securely access the second machine learning development platform;
receiving, by the server, an input via the first user interface; and
supplying, by the server, the input to the second machine learning development platform for generating a machine learning model, wherein the supplying is secured by the user credential.
2. The method of claim 1 , wherein supplying the input to the second machine learning development platform is performed in response to receiving the input.
3. The method of claim 1 , further comprising storing, by the server, an image associated with the second machine learning development platform, and using, by the server, the image to provision the second user interface.
4. The method of claim 1 , further comprising translating the input, by the server, resulting in a translated input, and wherein supplying the input to the second machine learning development platform comprises supplying the translated input.
5. The method of claim 1 , wherein supplying the input to the second machine learning development platform comprises supplying, via a first microservice associated with the first machine learning development platform, the input to a second microservice associated with the second machine learning development platform.
6. The method of claim 1 , wherein supplying the input to the second machine learning development platform is further secured by an encryption key generated in response to receiving the input.
7. The method of claim 1 , wherein the user credential is stored in a key-value store.
8. The method of claim 1 , wherein the input comprises training data usable to train the machine learning model.
9. The method of claim 1 , wherein the input comprises a data modification instruction to modify training data usable to train the machine learning model.
10. The method of claim 1 , wherein the input comprises a compute instruction that specifies compute operations to be performed by the machine learning model.
11. The method of claim 1 , wherein the input comprises a performance monitoring instruction that specifies performance monitoring of the machine learning model.
12. A server, comprising:
a processor; and
a memory that stores executable instructions that, when executed by the processor, facilitate performance of operations, the operations comprising:
provisioning a workspace comprising:
a first user interface for a first machine learning development platform that employs a first type of machine learning development tool for generating machine learning models, and
a second user interface for a second machine learning development platform that employs a second type of machine learning development tool that is different from the first type of machine learning development tool for generating machine learning models, wherein the first machine learning development platform is distinct from the second machine learning development platform;
receiving an input for the first machine learning development platform; and
in response to receiving the input,
generating an encryption key; and
using the encryption key to securely supply the input to the second machine learning development platform for generating a machine learning model.
13. The server of claim 12 , wherein the input is received via the first user interface for the first machine learning development platform.
14. The server of claim 12 , wherein the operations further comprise translating the input, resulting in a translated input, and wherein securely supplying the input to the second machine learning development platform comprises supplying the translated input.
15. The server of claim 12 , wherein securely supplying the input to the second machine learning development platform comprises supplying, using a first microservice associated with the first machine learning development platform, the input to a second microservice associated with the second machine learning development platform.
16. A non-transitory machine-readable medium, comprising executable instructions that, when executed by a processor, facilitate performance of operations, the operations comprising:
provisioning a workspace comprising:
a first user interface for a first machine learning development platform that employs a first type of machine learning development tool for generating machine learning models, and
a second user interface for a second machine learning development platform that employs a second type of machine learning development tool that is different from the first type of machine learning development tool for generating machine learning models, wherein the first machine learning development platform is distinct from the second machine learning development platform;
receiving an input for the first machine learning development platform, wherein the input comprises at least one of training data for training a machine learning model or a data modification instruction to modify training data employable to train the machine learning model; and
in response to receiving the input:
translating the input, resulting in a translated input; and
supplying the translated input to the second machine learning development platform for generating the machine learning model.
17. The non-transitory machine-readable medium of claim 16 , wherein the operations further comprise collecting a credential to securely access the second machine learning development platform, and wherein supplying the translated input to the second machine learning development platform is secured by the credential.
18. The non-transitory machine-readable medium of claim 16 , wherein the operations further comprise, in further response to receiving the input, generating a one-time use encryption key to securely perform the supplying of the translated input to the second machine learning development platform.
19. The non-transitory machine-readable medium of claim 16 , wherein receiving the input for the first machine learning development platform is conducted via a first application programming interface, and wherein translating the input and supplying the translated input to the second machine learning development platform is conducted via a second application programming interface.
20. The non-transitory machine-readable medium of claim 16 , wherein the operations further comprise storing an image associated with the second machine learning development platform, and using the image to provision the second user interface.