In the analytics departments of enterprise sized companies and organisations sits a lot of mathematicians, economics and statisticians. These are the people who are going to use ML to change the world, because business intelligence, prediction and analytics live in these departments.
Not a lot of these people can program.
I know a lot of programmers who want to work with ML, but in my experience, very few programmers are good enough at math or statistics to do so, and even fewer have the business skills to actually translate their results to management in non-tech based organisations.
I’m sure a lot of programmers will make excellent data-scientists, but I’m not entirely convinced why I would bring ML to my programmers rather than my people who have degrees in applied statistics and organisations.
I work in the public sector. One of the reasons ML hasn’t found it’s golden case yet, is largely because no one have figured out how to use ML in a way that is better than the decades worth of data-related work we have already done, and part of the reason behind this, is that companies who sell ML are programmers. They know how to use ML to identify, but none of them, not even IBM seem to know how to use ML for something they can actually get us to buy. And lord knows both sides of the tables have tried, I mean, even our political leadership has heard of the ML hype, and want us to use it. So I’m rather hopeful these tools for non-programmers will bring ML into the hands of people who will know what to use it for.
Not a lot of these people can program.
I know a lot of programmers who want to work with ML, but in my experience, very few programmers are good enough at math or statistics to do so, and even fewer have the business skills to actually translate their results to management in non-tech based organisations.
I’m sure a lot of programmers will make excellent data-scientists, but I’m not entirely convinced why I would bring ML to my programmers rather than my people who have degrees in applied statistics and organisations.
I work in the public sector. One of the reasons ML hasn’t found it’s golden case yet, is largely because no one have figured out how to use ML in a way that is better than the decades worth of data-related work we have already done, and part of the reason behind this, is that companies who sell ML are programmers. They know how to use ML to identify, but none of them, not even IBM seem to know how to use ML for something they can actually get us to buy. And lord knows both sides of the tables have tried, I mean, even our political leadership has heard of the ML hype, and want us to use it. So I’m rather hopeful these tools for non-programmers will bring ML into the hands of people who will know what to use it for.