1. Virtual Personal Assistants
Siri, Alexa, Google Now are some of the common examples of virtual personal assistants. As the name implies, they assist in obtaining information, when questioned over voice. All you need to do is stimulate them and ask, “What is my agenda for today?”, “What are the trains from Delhi to Mumbai”, or related questions. You can even command assistants for specific tasks like “Set an alarm for 7 AM next morning”, “Remind me to visit Visa Office day after tomorrow”.
For answering, your personal assistant looks out for the data, recalls your detailed queries, or send a request to other resources (like phone apps) to get info.
Machine learning is an essential part of these personal assistants as they gather and polish the information on the basis of your prior involvement with them.
2. Predictions while Commuting
Traffic Forecasts: We all have been using GPS navigation help. While we do that, our current locations and speeds are being stored at a central server for controlling traffic. This data is then utilised to create a map of the current traffic.
While this helps in anticipating the traffic and congestion analysis, the underlying difficulty is that there is less number of cars that are provided with GPS. Machine learning in such situations helps to predict the regions where congestion can be found on the basis of daily experiences.
Online Transportation Networks: When booking a cab, the app determines the price of the ride. When sharing these services, how do they minimize the deviations?
The answer is “ Machine learning ”
Jeff Schneider, the engineering lead at Uber ATC reveals in an interview that they use ML to define price surge hours by predicting the rider demand. In the complete circle of the services, ML is performing a significant role.
3. Social Media Services
From personalizing your news feed to more suitable ads targeting, social media platforms are using machine learning for their own and user privileges. Here are a few samples that you must be seeing, practising, and enjoying in your social media accounts, without recognising that these amazing features are nothing but the applications of ML.
- People You May Know:
Machine learning runs on a simple concept: understanding with experiences. Facebook continuously sees the friends that you connect with, the profiles that you hit very often, your interests, workplace, or a group that you share with someone etc.
On the basis of constant learning, a list of Facebook users are recommended that you can become friends with.
- Face Recognition:
You upload a picture of you with a friend and Facebook instantly recognizes that friend. Facebook compares the poses and projections in the picture, notice the unusual features, and then match them with the people in your friend list.
The entire process at the backend is complex and takes care of the accuracy factor but seems to be a mere application of ML at the front end.
- Similar Pins:
Machine learning is the kernel element of Computer Vision, which is a technique to derive useful information from images and videos.
Pinterest uses computer vision to recognise the objects (or pins) in the images and suggest similar pins accordingly.
4. Product Recommendations
You shopped for a product online a few days back and then you keep receiving emails for shopping suggestions. If not this, then you might have seen that the shopping website or the app prescribes you some items that anyhow suit with your taste.
Assuredly, this improves the shopping experience but did you know that it’s machine learning creating the magic for you? On the basis of your action with the website/app, earlier purchases, items wished or added to cart, brand preferences etc., the product suggestions are made.
5. Online Customer Support
Plenty of websites nowadays give the option to chat with customer support spokesperson while they are driving within the site.
However, not every website has a live executive to solve your queries. In most of the crises, you chat to a chatbot. These bots manage to secure information from the website and present it to the customers. In the meantime, the chatbots advance with time.
They tend to follow the user queries better and serve them with more reliable answers, which is plausible due to its machine learning algorithms.
The world is simply being reshaped by machine learning.
As machine learning is becoming more complicated, we’ll see extended usage of robots. Robotization depends on machine learning for achieving various purposes, including robot vision, self-supervised learning, and multi-agent learning.
Soon, we suspect robots to become more intelligent at performing tasks. Drones, robots in manufacturing positions, and other types of robots are likely to be adopted frequently to make our lives more prosperous.
Machine learning is one of the most groundbreaking technologies of the 21st centenary. Although this technology can still be held to be nascent, its future is intense.
In the upcoming years, we are inclined to see more high-level applications that amplify its capabilities to unbelievable levels.
Best Jobs of 2021
According to a statement from job site Indeed, machine learning engineer is the best job of 2019 due to rising demand and great salaries.
The career boasts a current average salary of $146,085 with a growth rate of 344 per cent last year.
Roles such as software developer continue to rank highly due to a high number of job openings, but machine learning engineer roles claim the number one spot due to higher salaries and faster growth.
Hurry ! Machine Learning Engineers are in demand !!