From voice assistants to self-driving cars, Machine Learning is changing not only the way we interact with machines but also how we connect with the world. Machine Learning is becoming one of the hottest technologies in the current market and making applications and services smarter and better every day.
Have you ever wondered how Facebook & Instagram suggest people you may know or Amazon product recommendations that you may interested or willing to buy? Well, it’s all possible because of Machine Learning. The technology is used to process a huge amount of user data such as search history, content interactions, to offer personalized data and products that we see.
Over 2.5 quintillion bytes of data we are creating every day, and it’s only going to increase from there. This huge amount of data can’t be handled and managed by humans physically and this is where Machine learning gets involved.
Machine learning is an application of artificial intelligence, that can be explained as automating and improving the learning process of computers based on their experiences without being explicitly programmed. It works similar to the human brain, which continues learning and finds the solution for different problems. Machine Learning is different from the traditional programming where programmers give input and logic to solve any problem but in Machine learning rather than telling a computer exactly how to solve a problem, the programmer instead tells it how to find patterns and create logic to solve the problem itself.
Machine learning is an advanced application of statistics to learning to identify patterns in data and then make predictions from those patterns. The primary aim of Machine Learning is to allow computers to learn automatically without human interference. And one of the most exciting technologies that one would have ever come across.
The changing face of Industries with Machine Learning
Machine learning has little to do with human intelligence. And this is a technology that learns through data training and processes inputs in order to apply different approaches. It uses two types of machine learning algorithms, supervised learning algorithm, which trains a model on known input and output data so that it can predict future outputs, and unsupervised learning algorithm, which finds hidden patterns in input data. And it instructs an algorithm to learn for itself by analyzing data.
Machine learning is one of the current innovations that has helped us upgrade not only industrial and professional development but also advances our everyday living.
In the transport industry, Machine learning work with different features of the application like collecting and analyzing data from previous transactions. After analyzing the huge amount of user data ML can discover purchasing patterns of different users, how frequently they buy tickets or certain monthly passes that could be helpful for the service provider to offer gifts, discounts to the users for developing better relationships with customers.
Machine learning technologies can reinforce the efforts of traditional medical practices, Al has already begun tackling some of medicine’s most incurable problems, and allowing researchers to better understand genetic diseases by using predictive models.
Previously, doctors and health professionals were following a traditional way to review the stack of data manually before they diagnose any patient. Deep learning models quickly provide real-time insights and, combined with the explosion of computing power, are helping healthcare professionals diagnose patients faster and more accurately.
Banks and many other financial institutions are utilizing automated processes, Machine Learning is currently driving some of the biggest industry changes in banking, finance and insurance. Today, Machine Learning has come to play an essential role in many phases of the financial world, from approving loans, credit score to determine risks.
Machine learning can analyze high-volume data. Offering solutions for identifying and preventing fraudulent transactions, financial companies must abandon the outdated path and include Machine Learning in their process to win the war against financial fraud.
Machine Learning (ML) in our everyday life :
There are many big institutions which have already implemented ML in their product and services and exploring new ways using this advanced technology to build better products.
Google has already implemented ML in its search engine and Google maps. When you start typing any keyword in the search box it automatically assumes what you might be searching for and provides suggested search query. And the suggestions could be based on your past searches, what is popular now, or what is your geographical location.
Netflix uses the watching history of users with similar tastes to recommend what you may be most interested in watching next. And this the most well-known feature of a Netflix, users who watch A are likely to watch B.
Netflix uses thousands of video frames from an existing tv series or movie for thumbnail generation, and later annotates these images then ranks each image in an effort to analyze which thumbnails have the most clicks. Using thumbnails to create user attention in order to get more click.
Uber’s decision-making is completely data-driven with machine learning. Uber is taking advantage of ML in many ways to improve the customer experience with its services. When you enter your destination or drop point, the app shows you suggestions based on your ride history and regularly travelled destinations. This is how Uber using ML to establish a relationship with the business process.
Automation is playing an important role in our lives. As the innovation are expanding with AI and ML, and these technologies are combining to create innovative solutions in every field imaginable. And making our lives better every day.
The technology still isn’t perfect in many cases, the world is constantly being reshaped by machines possessing intelligence and making our lives easier. The very concept of ML is continuously improving, we believe that human and machine can do a lot together and possibilities are exponential