Self-driving cars and the technology that powers them has captured the imagination of the world, and for a while we all thought cars would drive us instead of us driving them.
This is a subject that’s close to our hearts. Udacity’s founder, Sebastian Thrun, is a leading innovator of self-driving car technology. He led the development of Stanley, which was the winner of the 2005 DARPA Grand Challenge, and prior to Udacity, he founded Google X and the company’s self driving car team.
With that said, we’ll look back at how the technology has been applied since its inception, and what’s on the horizon for self-driving cars.
When browsing Stack Overflow for answers to your programming questions, you’ve likely come across charges against certain code as “unpythonic,” or praise of one solution as “more Pythonic” than another. But what do developers mean by these terms? In this article, we’re going to take a look at Pythonic style, first defining it and then showing you how you can — and why you should — learn about it.
Podcasts are the next big thing. It has been reported that podcast listeners spend more than six hours per week tuned in to podcasts. This is not surprising at all — what do you do when you are working from home with your earplugs tugged in, or when you are cooking your favorite meal or before you go to sleep? Most likely, listening to podcasts!
Podcasts are easy to access and offer the flexibility to multitask. And in a world where you are constantly doing something or another , what else do you need to consume your favorite content? So much so, that last year even Netflix tried its hand at podcasts. As they say, everyone and everyone’s roommate is doing a podcast! 😉
But in a sea of podcasts available across different genres, how do you choose the most relevant one? It’s a challenge for sure.
If tech podcasts are your thing, here are five that we think you should listen to in 2020.
Many of the modern computer vision applications rely on deep learning algorithms. Therefore, selecting and using datasets to train those deep learning algorithms is an essential skill for any computer vision engineer.
In this article, we’ll take a look at how computer vision datasets have refined the field of object identification and contributed to high-tech inventions like self-driving cars and the latest smartphones.