Why machine learning models fail - SD Times

Granade predicts that those companies that find themselves behind the curve on data science and machine learning practices will work quickly to correct their mistakes. Organizations that have tried and failed to implement this kind of technology will keep their eye on the others that have succeeded and take tips where they can get them. Not adapting to this practice isn't an option in most industries as it will inevitably lead to certain companies falling behind as a business. Granade goes back to a comprehensive approach as the key to remedy the mistakes he has seen. "I think you can say'we're going to invest as a company to build out this capability holistically. 'We're going to hire the right people, we're going to put a data science process in place, and the right tooling to support that process and those people,' and I think if you do that you can see great results," he said.