2020 is a special year for all Americans — it is the year of the US Census. The US census is one of the biggest population surveys in the world and is mandated by the US constitution. It takes place every ten years and helps the government decide where to build and maintain schools, hospitals, transportation infrastructure, and police departments to name just a few. All in all, the various censuses determine the allocation of over $400 billion in federal funds every year.
In this post, we explain how bias and noise in machine learning are two sides of the same coin.
God does not play dice. — Albert Einstein
Einstein famously gave this statement in reaction to the emerging theory of quantum mechanics, which seemed to defeat the fundamental laws of physics. Read on to see how the same goes for the fundamental laws of machine learning.
Before getting into it, let’s briefly review the classical bias-variance-noise tradeoff. …
In this post, we explain the bias-variance tradeoff in machine learning at three different levels: simple, intermediate and advanced. We will follow up with some illustrative examples and discuss some practical implications in the end.
If you can’t explain it simply, you don’t understand it well enough. — Albert Einstein
Understanding the bias-variance tradeoff can be a bit tricky at first as it involves several quantities that are never available in practice. Nonetheless, it provides insights into best practices for optimizing real-world machine learning applications.
The prediction error of a machine learning model, that is the difference between the ground…
This comprehensive and easy three-step tutorial lets you train your own custom object detector using YOLOv3. The only requirement is basic familiarity with Python.
As an example, we learn how to detect faces of cats in cat pictures. Given the omnipresence of cat images on the internet, this is clearly a long-awaited and extremely important feature! But even if you don’t care about cats, by following these exact same steps, you will be able to build a YOLO v3 object detection algorithm for your own use case.
Crypto is back and Bitcoin leads the way!
Slowly but steadily, crypto climbed back towards its old records. Even though prices are still well below the Jan 2018 crypto bubble hype, Q2/19 trading volumes are three times as high as Q1/18!
Apart from record trading activity, by crunching numbers of 184 digital asset exchanges we identified the following global trends:
After 2017’s Crypto-Optimism and 2018’s Crypto-Pessism, it is time for Crypto-Realism.
After a year of lower and lower prices, crypto has made its long-awaited come-back. In Q1/19, both trading volumes and overall digital asset prices increased and show a strong upward trend. Most notably, prices of four of the Top 10 most traded digital assets increased by more 25% — gains which haven’t been seen since 2017.
Crunching numbers of 192 digital asset exchanges worldwide led to the following key findings:
When Moon and when Lambo? Not in 2018!
To put it short — 2018 left a lot to be desired. Any planned trip to the moon had to be canceled and the drive back from the airfield was in an Uber. When the hype train of 2017 came to a standstill many investors felt that crypto is over. But is that really true?
To find out we crunched numbers of 178 digital asset exchanges* worldwide and arrived at the following key findings:
Last week’s contentious Bitcoin Cash hard fork was the likely reason for one of the biggest sell-offs in the cryptocurrency market in the past year. In this short article, we recap what happened and where we are right now.
What is A Hard Fork?
In simple terms, a hard fork of a digital asset network happens whenever the underlying protocol is changed in a way that makes it incompatible with the existing protocol. In this case, any miner that runs the original software will no longer accept blocks created by miners running the “updated” mining software and vice versa. …
The wait continues ….
To put it short — Q3 left a lot to be desired. Both trading volumes and digital asset prices continued their 2018 downward trend. Overall, trading volumes are now only half as high as in Q1. Nonetheless, they are still almost twice as high as in Q3/2017.
Crunching numbers of 159 digital asset exchanges* worldwide led to the following key findings:
Deep Learning Magic