Applied AI Course Machine Learning

Image Recognition is one of the key techniques that bring out the essence of Applied AI Course Machine Learning capabilities for a wide range of industries such as scientific research, geo-targeting, space innovations, mining, and surgical procedures.

New-age applied AI and machine learning capabilities are transforming the way we deal with complex challenges in our lives. Machine Learning is widely used in various specializations such as IT Automation, Industrial Robotics, Healthcare Imaging and Diagnostics, Smart City infrastructures, and so on. 

Image Recognition Saves Millions of Lives Every Year

Image recognition used in healthcare and diagnostics is called ‘Medical Imaging’. In the last 10 years, we have seen countless innovations in Applied AI and Augmented intelligence techniques that help doctors manage critical cases more efficiently with predictive analytics, data visualization, and patient monitoring.

Medical Imaging uses AI to sift through billions of data points mined from pools of scans, diagnostics, and research papers to quickly unravel the mystery behind the patient’s health conditions. Using Applied AI course machine learning techniques with image recognition, the doctor is accurately able to detect the exact nature of damage to the body and how the condition could further deteriorate if assistive technologies are not administered in time.

Security and Citizen Identification 

In India, UIDAI uses biometric capabilities to identify the registered citizens, providing them with a unique identification number, similar to the Social Security Number (SSN) in the US. Many nations are planning to deploy image recognition-based techniques to improve their citizen identification platforms and use it to facilitate social services and applications, including passport approvals, insurance, medical administration, traffic management, passenger movement, and so on. 

In addition, image recognition techniques are also used with IoT and city cameras to further improve the security and surveillance against threats, terrorism, and natural calamities. 

UI UX in gaming and e-learning

Almost every digital platform is inspired to transform its UI UX according to gamification standards. However, gaming itself continues to be on a disruptive path. Gaming platforms are embracing the power of Facial Recognition, Image Processing, and Deep Learning to deliver high-quality, highly immersive gaming experience. For example, Niantic’s Pokemon Go.

Gaming platforms also use image recognition techniques to build powerful mobile app-based configurations to ensure the gamer experiences a highly responsive image during every interaction.

Similarly, techniques are used in many e-learning and online programming courses that specifically teach engineering, medical, and other experiential subjects, which require OCR, or elemental studies of the samples.

Although very compelling to work with, the existing user case scenarios in Image Recognition are hugely complex and require candidates and professionals to demonstrate their experience in IT Cloud computing, Big Data Analytics, Reinforcement Learning, and Computer Vision.

Self-Driving “Everything”

I have an AI-driven car– which is probably the most AI intensive automobile in the passenger vehicle segment. We already have a Voice-controlled car ignition system in addition to in-car experience (music, AC control, driving assist, geo-tracking, and so on). What I like the most about the car is its object detection system that identifies an obstruction 50 meters ahead on its path. The braking and alert system works in sync with image recognition and predictive software systems. 

‘The Machine Car Brain’ works like a neural network with sensors, cameras and alert systems to safeguard the passengers, the car body, and the pedestrians directly in the line of the collision.

Today, we hear about self-driving cars and trucks, mostly thanks to the work of Elon Musk’s Tesla! Tesla belongs to the same stable of companies that also has SpaceX in its brood — the proud space research and propulsion management company that recently successfully launched the first commercial space travel excursion to the International Space Station (ISS) in partnership with the NASA.

The Conclusion

There are over 50+ reliable Applied AI building tools and kits that serve the frontline tech industries. Medical imaging alone brings in billions of dollars to the Applied AI DevOps– and provides jobs to some of the most talented groups of RL Trainers, analysts, programmers, and AI engineers. If you are working in the IT automation industry or plan to do so in the future, your certification with Applied AI projects could enhance your skills in the healthcare, gaming, and mobile app industry. 

Thankfully, unlike other fad technologies that are cost-intensive, these Applied AI techniques are still under development and it may take many more years of training and development before they get refined results.