I mentioned in an earlier post some free Amazon resources that are available for managing AI projects - I think those are really valuable and they are still available here:
These are really good for getting an overview of what a typical machine learning project looks like.
If you are interested in going a little more in depth and seeing the guts of what machine learning looks like it is worth taking a look at the TensorFlow tutorials:
There are five links on the bottom of the page that will take you to 5 different tutorials, I'm currently on the third, but it is very educational.
In one sense, these aren't for the faint of heart. They are really doing real machine learning, and if you're like me, you won't understand some of it. That's OK.
You need to look past a few things you don't know and just plow ahead they really do give you a great idea of how machine learning actually works.
Unlike the Amazon courses, which don't really require any prerequisites, you probably need some experience with development tools to get through the TensorFlow tutorials. They require that you are comfortable clicking a Play button like you run across in development environments, and sometimes you are kicked back warning messages that you have to look at, stomach, and promptly ignore.
While I've tweaked a couple of print statements to get the notebooks to show me different stuff, I'm really not messing with the core of what the notebooks do. I can generally make sense of it, but I don't have the skill to change the core logic of what these are doing.
I actually very much appreciate the concept of the notebook - it forces documentation into your work in a much more direct kind of way than traditional programming where comments and documentation are often an afterthought. Every example I've come across has had lots of helpful information (they are tutorials) and the text that is presented alongside the code is indispensable.
If you want to know more about machine learning, and you aren't afraid to see how the sausage gets made, it is worth checking it out. Highly educational.
Amazon has recently opened up some of its internal AI education resources for anyone who wants to use them. They're freely available on its learning platform, which you can use if you have an Amazon account.
I'm currently working through the Machine Learning for Business Challenges course, which has some great content. It's available here:
The basics of ML explained in a non-technical way with lots of useful examples
What kinds of problems are good for ML and which aren't
What kinds of questions to ask to make sure your team is thinking about an ML problem the right way
How to define the scope of a ML solution
The lessons are succinct and digestible, with lots of demystification and straightforward examples that show you how machine learning can benefit you, and when it probably isn't the right solution.
Here is a link to all the business decision maker classes:
You've worked at a business for several years, you're really starting to understand how it works. You're grokking it. You're gaining a deep understanding of the innerworkings, outer-workings, and every kind of work-between.
And you suddenly have it - a moment of insight - a blinding flash that helps you to solve a problem you've been stuck on.
They're great when the happen. But how often do they really occur for you? For the lucky, perhaps several times a year. For the rest of us, less often.
One of the great promises of AI is to be able to achieve these types of insights faster and more repeatedly by asking the right questions.
AI will allow us, as it becomes more ubiquitous, to ask better questions and find the answers faster.
Here are the stages of inspiration and insight as we move forward with Assisted Inspiration (we need a new acronym).
Human-Only Insight - the amazing and super-powerful capability that we humans possess to understand our world and make amazing leaps forward. Pattern recognition, dreams, emotional resilience, quantum gravity. It's all part of it.
Tool Assisted Insight - explicit use of math and spreadsheets and literature to figure stuff out, in addition to our own powerful minds.
AI Assisted Insight - use of machine learning and other sophisticated computer tools to value information and create models for problem solving.
As we get better at formulating our questions, generating and processing data, and creating these models - as these skills become more pervasive in the workforce - then the pace of AI Assisted Insights is only going to INCREASE. Think the world is going fast now? Think it's changing? Think we're in a VUCA phase?
Buckle your seat-belt. As our kids join the workforce and spend less time writing code (it probably really will happen this time) and more time thinking about problems and using AI to assist them, the more the pace of change will accelerate.
Will this be challenging at times? Yes, definitely. It also represent a fundamental new phase of work, life, and society.
What an amazing time to be alive.
I've been lucky enough to have some human-only and data-assisted insights in my life. Those moments are joyful when they occur. They are real breakthroughs when you see things in a whole new light.
Imagine having more of those. More breakthroughs. More insight. More inspiration. It will be challenging, and for those of who are willing to face these challenges a broad new plateau of opportunity and human potential awaits us.
Jonathan Fries on .