Artificial Intelligence (AI) has big implications for healthcare. This has been brought to light by the current global COVID-19 pandemic that has overloaded hospitals, stretched resources, and infected millions of people before tests and treatment could be made available.
AI-driven technology has been in development for the healthcare community for many years. For example, AI can be used to enhance 2D and 3D imaging to better detect abnormalities and improve diagnosis. However, there are still some challenges with how AI can be applied to healthcare.
First introduced back in the 1950s, AI has evolved tremendously over the past 65 years. While initially it was used in more technical settings, like specialized computer labs, adoption has grown to the point where AI is integrated in our everyday lives.
With AI becoming part of how we work and live, it’s important to understand how it will be used in our day-to-day lives and how you can make an impact in the industry.
Self-driving cars are no longer just a part of science fiction movies. If you visit San Francisco, odds are you will see a self-driving car from Uber or Cruise roaming the streets — with a supervisor sitting behind the wheel, of course.
Tesla has been selling cars with self-driving capabilities for years. Their Autopilot feature can “steer, accelerate and brake automatically” and even be summoned within a parking lot.
If you shop for a car in 2020, you’ll be able to choose from multiple options that can self-park. In fact, they can probably pass their parallel parking driver’s test better than you can!
In order to understand the industry uptake of this emerging technology, we connected with some of our alumni of the Intro to Machine Learning with PyTorch Nanodegree program. Here’s what they said about the impact of the Nanodegree program on their lives.
“Today I work as a machine learning engineer, it’s like a dream come true,” chuckles the very excited Omkar Sahasrabudhe. Omkar moved from being an intern to a Web Developer and now a Machine Learning Engineer in just a little over a year. This is his story.
The field of machine learning continues to boast incredible job growth, salaries, and skill sets that can be used in many different industries. Google utilizes this technology in their Cloud product to allow startups to build machine learning models that work on data of any size, while GE utilizes IoT to help detect and prevent anomalies and crashes in their products. These are just a snapshot of the numerous applications of machine learning in the market today that display the potential for an exponential amount of professional expansion. Currently, just in the US alone, there are over 50,000 open roles for machine learning professionals, so now is the time to develop machine learning expertise!
In LinkedIn’s 2020 Emerging Jobs report, AI Specialist, a role that includes machine learning, deep learning, TensorFlow, and Python as key skills, boasts 74% annual growth. All of the above skills are incorporated into Udacity’s new Intro to Machine Learning with TensorFlow Nanodegree program, which is a great way to get introduced to the fundamentals of machine learning, including areas like manipulating data, supervised & unsupervised learning, and deep learning.
So what is TensorFlow, and how is it being utilized today? TensorFlow is a deep learning framework made by Google for creating machine learning (ML) models that use multi-layer neural networks. The TensorFlow library allows users to perform functions by creating computational graphs. AirBnB utilizes TensorFlow to improve the guest experience to categorize listing photos by classifying images and detecting objects at scale. Coca-Cola uses TensorFlow to enable mobile proof-of-purchase at scale, while PayPal uses TensorFlow to detect fraud, and Twitter uses TensorFlow to rank tweets, highlighting the broad and powerful range of applications.