As a beginner in artificial intelligence, it can feel overwhelming with the number of things you have to learn. The best way to learn is to get down and dirty, get some hands-on experience, and start building. Here are seven project ideas for you to get started. To get started, an easy project you can start with is a system that can recognize handwritten digits with the help of artificial neural networks. Digits written by humans vary widely in shape, size, and style.

GUVI has joined hands with AICTE to offer free online training for Artificial Intelligence professionals or students. AICTE with the partnership with GUVI is offering free online Artificial Intelligence to the participants that will be a 90 minutes workshop. The event will start from April 24 2021 6 PM IST to April 25 2021 at 6 PM IST in different time slots for participants. The aim behind the event is to help the students to polish their Python skills and develop the face recognition app. The training is an initiative taken by AICTE and GUVI to help the professionals of India to top the Artificial Intelligence domain.

There Is a Range of Tasks Your Face Recognition App Can Be Designed to Perform If You Use the Right Face Recognition Methods. The Facial Recognition technology has been one of those, gaining ground fastest over recent years and one that is still, obviously, pretty far from its heyday. Invented to, virtually, enhance, or rather, extend one of the 6 human senses, it is finding new, often, critically important (for example, public security-related) uses and becoming more wide-spread globally by the day. According to Researchandmarkets.com, the total worth of the global Face Recognition software market is estimated to have constituted some USD 3.85 billion in 2017 and it is predicted to reach USD 9.78 billion in 2023, thus showing a nearly threefold growth. This can only mean that while giving those better equipped with Face Recognition apps an edge and an additional means of control, the rapidly developing Facial Recognition technology is also becoming a competitive factor for businesses in various industry sectors.

The FoodVisor app harnesses the image recognition power of deep learning convolutional neural networks to recognize the food on a plate. "CAUTION" my iPhone warns me, highlighting the word for good measure in a bright red circle. No, I wasn't about to overuse my data plan, or even try to make sense of a Donald Trump tweet. Instead, I had, like some Instagram-obsessive, just taken a photo of my breakfast for the first time, and an artificial intelligence (AI) resident on my phone didn't like what it saw. My poached eggs and toast also included … a sausage.

The Facial Recognition Technology Is Known to Have Gained a Foothold in Many Industry Verticals and It Keeps on Continuously Charting New Ground. Facial Recognition has gained so much traction in an entire host of verticals and applications (according to Variant Market Research, its market is expected to be worth some $ 15.4 billion by 2024) that most anyone, regardless of the kind of business they are in, should look into whether the technology could come in handy in reaching their business objectives. In part, this is owing to the ability of the Facial Recognition technology to better equip and advance the field of expertise known as Marketing, - something universal and of the utmost importance to most industries. Moreover, Face Recognition can make a dent in precisely those areas of Marketing, in which the now rampant Digital Marketing falls short, or is, simply, irrelevant. What are those areas, how much headway has been made already and what are the potentialities one should be aware of?

There Is a Range of Tasks Your Face Recognition App Can Be Designed to Perform If You Use the Right Face Recognition Methods. The Facial Recognition technology has been one of those, gaining ground fastest over recent years and one that is still, obviously, pretty far from its heyday. Invented to, virtually, enhance, or rather, extend one of the 6 human senses, it is finding new, often, critically important (such as, for example, its role in the war on terror) uses and becoming more wide-spread globally by the day. According to Researchandmarkets.com, the total worth of the global Face Recognition software market is estimated to have constituted some USD 3.85 billion in 2017 and it is predicted to reach USD 9.78 billion in 2023, thus showing a nearly threefold growth. This can only mean that while giving those better equipped with Face Recognition apps an edge and an additional means of control, the rapidly developing Facial Recognition technology is also becoming a competitive factor for businesses in various industry sectors.

Apple this week unveiled its new iPhone X, and with it, a host of security concerns. Apple this week unveiled its new iPhone X as part of the smartphone's 10th birthday, and with it comes a host of security concerns. One of the major features of the iPhone X (X for the roman numeral 10) is FaceID, a facial recognition feature for unlocking the phone by just looking at it. Apple has a solid track record on personal privacy when it comes to securing its devices, but FaceID raises major issues, such as whether the tool be used against an owner's will to gain access to their phone or what happens if a hacker steals your facial identity? A staff attorney with the American Civil Liberties Union argued that law enforcement could use someone's face against their will to unlock their phone, possibly without violating the person's' Fifth Amendment right against self-incrimination.

Google has purchased Moodstocks, a French startup that specializes in speedy object recognition from a smartphone, showing (again) the search giant's intense interest in AI. Unlike other products (including Google's own Goggles object recognition app) Moodstocks does most of the crunching on your smartphone, rather than on a server. While Google seemingly has some pretty good image-spotting tech already, like the canny visual categorization in Photos, it says it's just getting started. "There is still a long way to go [with machine learning], and that's where Moodstocks comes in," the company said in a blog post (translated). The deal seems to fall in to the "aqui-hire" category, as Moodstocks will cease its own recognition services, and its team of engineers will join Google at its R&D center in Paris. Google is rumored to be working on a feature that allows Android users to search directly from their photos (below), though the company didn't say if the acquisition is related.