The fusion of blockchain and machine learning is an ultimate game changer. Machine learning relies on high volume of data to build models for accurate prediction. A lot of the challenges incurred in getting this data lies in collecting, organizing and auditing the data for accuracy. This is an area that can significantly be improved by using blockchain technology. By using smart contracts, data can be directly and reliably transferred straight from its place of origin. Smart contracts could, however, improve the whole process significantly by using digital signatures.

Blockchain is a good candidate to store sensitive information that should not be modified in any way. Machine learning works on the principle of “Garbage In, Garbage Out,” which means that if the data that was used to build a prediction model was corrupted in any way, the resultant model would not be of much use either. Combining both these technologies creates an industry disruptor which leverages the power of both Blockchain and Machine learning.

Automated Machine Learning (AutoML) provides methods and processes to automate the end-to-end machine learning workflow towards solving real-world business problems.

In traditional machine learning world, data scientist used to spend a considerable amount of time in Data wrangling, model selection and tuning, now with the advances of AutoML it provides methods and processes to make Machine Learning available for non-Machine Learning experts, to improve efficiency of Machine Learning and to accelerate research on Machine Learning.

Automating the end-to-end process of applying machine learning offers the advantages of producing simpler solutions, faster creation of those solutions, and models that often outperform models that were designed by hand.