You have an idea, or you’re looking to solve a problem. And you have, in your mind, already worked out how you want your product or solution to work.
All you need now is for someone to build it for you.
So, you look for a software development agency.
You speak to a few companies. You even like a few of them. You tell them your requirements, and you get quotes.
Some of them are amazing. For $20,000, you’ll get your entire solution built for you. All you have to do is wait 3 months.
Fast forward 6 months, or…
A very common challenge we encounter for e-commerce businesses, is that users are, in fact, terrible at finding the item they like.
Let me tell you a story about Michelle.
Curriculum learning. Sounds exactly like what happens when you go to school, right? It is. And it turns out that it helps machine learning systems learn better too.
Seems like we got something right when teaching ourselves.
By and large, machine learning systems, whether they use simple neural networks, or use deep learning, or anything else that you may have heard of, mostly emphasize a lot on 2 things:
The quality of data is of course extremely important. “Garbage in, garbage out”, you may have heard before. It applies to machine learning as well…
AI, or more specifically machine learning, can sometimes seem like an incredibly powerful thing that does all kinds of stuff.
But to understand it, it helps to break it down into its key features and capabilities. We’ve identified 6 of these, and you’ll find that more often than not, machine learning systems really implement 1 of these features.
Here’s the 6 capabilities:
Truly powerful and successful systems even combine these together, to become even more versatile and accurate.
Personalization and profiling systems use machine learning…
Remember that AI or machine learning is not the right solution for every type of problem.
There are certain problems that machine learning solves really well.
But there are also other problems that machine learning really isn’t the best, or even the right, solution.
We’ll give you 1 very easy way to know whether you should not use machine learning.
If you can describe exactly the rules to solve something, don’t use machine learning.
A clear signal not to use machine learning.
The key here is that if you are facing a problem that can be solved, 100%, with pre-determined…
So you’ve decided to build an app.
Maybe that’s because you’re an entrepreneur and you have a new idea that is going to change, or disrupt, the world.
Or, maybe you’re a seasoned business owner and you’ve identified just the process to automate to scale up your business.
Or, maybe you’re a marketing professional who’s going to scale your business and put your products and services in the hands of everyone through an web or mobile app.
Or, maybe you’re the CxO of an MNC who is taking the next step in your masterplan to modernize and digitalize your entire…
If you’ve ever tried having anything custom-built, you know it’s not a trivial process. Clothes. Packaging. Furniture. Interior design. Cars.
It sounds easy enough, right? You interview a couple of folks who can do it for you, you tell them what you need, you cough up some dough, you wait a while with great anticipation, and presto, your perfectly built, one-in-the-world, form-fitted item gets delivered to you, complete with a bow on top.
And then you start using it, and realize all the wondrous benefits it brings you, by being just right.
The fact is…
Regex. Regular expressions.
You may have heard of them, maybe you dabbled a bit with them. But they always seem to hard to get right, don’t they?
Let me try to make it simple.
There are many ways to denote the start and end of a regular expression. But a very common one is to enclose them with the
/ symbol. Like so:
This way, it’s easy to see where a regex starts and ends.
A long time ago, when I first started to study machine learning models, the sheer number of different models and techniques was bewildering.
What I needed was a bird’s eye view of what all these different models and approaches do, what they were good at, and what they weren’t so good at.
So today, I’m going to break it down at a very simple level.
The internet is a scary place. You know that, whether intuitively, or because you’ve experienced some of the dangers first hand. Perhaps a devilish piece of ransomware got you and shut off your access to your data unless you paid something. Or perhaps you’ve experienced your Facebook or your Twitter account getting hacked, your password changed, and you had a nerve racking time undoing the damage, all while hoping that the guy who took control of your account wasn’t doing damage to your reputation online. …