There is quite a number of different combinations that are currently investigated and partially also used (so this list is not exhaustive, it gives a few examples):

• Machine Learning uses data and block chains can help to establish a data provenance, ensuring only "good" data is put into the model training. The benefit is here the quality of data.
• Privacy-by-design: ML systems that are trained via transferred blockchain data, to make sure the data is kept secretly. Here the benefit is data security.
• Contrarily, you can use a block chain, to store the different evolving states of a machine learning model, as it is retrained. The benefit is the recreation of each state of the model - which is almost identical to storing source code in a version control system.
• Extending the last approach, you can store running programs, e.g. a ML model in the blockchain and use the chain to make sure the program code is not manipulated.

There is also a good overview article by Sgantzos and Grigg, "Artificial Intelligence Implementations on the Blockchain. Use Cases and Future Application", Future Internet, 2019, 11, 170 - doi:10.3390/fi11080170.

Hope that helps,

Marcus

Dear Rahul Pandya

This articles might be helpful, have a look:

1. Article Integration of Blockchain, IoT and Machine Learning for Mult...

2. https://www.bbvaopenmind.com/en/technology/artificial-intelligence/blockchain-and-ai-a-perfect-match/

Kind Regards

Qamar Ul Islam

Machine learning always works on data so there needs more security. that's the reason integrated machine learning and blockchain. we know blockchain is more secured.