Machine learning (ML) is an application of Artificial Intelligence (AI) that provides the system with the ability to automatically learn and improve from experience rather than explicit programming. This is possible because today a large amount of data is available which lets machines to be trained rather than programmed. It is considered a major technological revolution that can analyze a massive amount of data.
Almost everything coming out of the technology world these days seems to have an element of artificial intelligence or machine learning (ML) in it. ML today is the implementation of some aspects of human abilities but certainly not the entire potential for human intelligence. ML enables people to accomplish more by collaborating with smart software. It is like putting more human face to technology. The whole world is debating the consequence of AI/ML and how it will impact our future. Telsa Inc. CEO Elon musk and Alibaba group holding ltd chairman Jack Ma had an around this recently.
Everyone who is in the programming industry or not in programming industry but want to know and grasp the knowledge of what is data science, machine learning, and Artificial Intelligence, These three are the biggest areas where everyone is looking to build their career, As Machine Learning Engineer is getting a highest paid off as research by TechRepublic, Becoming an ML Engineer you need to gain machine learning certification as well.
Machine learning is changing the world by transforming all segments including healthcare services, education, transport, food, entertainment, and different assembly line and many more. It will impact lives in almost every aspect, including housing, cars, shopping, food ordering, etc. Technologies like Internet of Things (IoT) and cloud computing are all growing implementation of ML to enhance objects and gadgets into “smart” for themselves. ML offers potential value to companies trying to leverage big data for customer satisfaction. The hidden pattern buried in the data can be very useful for business.
Most of our decisions on social media are impacted by ML. From feeds that we see on the timeline to notifications that we receive from the social media apps, everything is curated by ML. While we travel, work, live life our decisions are examined by machine learning to provide us with a better experience. ML takes all the past behavior, web searches, interaction and everything else that we do when we are on these websites and tailors the experience for us. It helps enhance our web surfing into a personalized one. Whether we use Spotify, Netflix or YouTube ML is making a decision for us. The recommended video list on youtube, recommended shows on Netflix or pre-created playlist on Spotify or any other media or music streaming service are all done by ML programs. Smart search engines that can optimize our search with a keyword search or respond to human speech (Siri, Cortana, and Google Now) are also an outcome of ML algorithms.
Managing data can be crucial in the field like education. Smart classrooms have been developed into expanding the database of resources. Digital system can record every individual performance and can provide an accurately customized report of their specific need. With classroom strength increasing day by day this kind of technology help will be a breakthrough in education. This will ease the burden on both teachers and students. This does not mean teacherless classroom as no computer or robot can fulfill the multiple roles that a teacher plays, however, some of the tasks can be automated through machine learning.
Machine learning integrated alarm system and surveillance cameras are very popular today. ML uses facial recognition technology to build a catalog of frequent visitors at home and recognizes unusual visitors. It can tell the working parents when kids get back home and can even call for emergency services.
Automation of our domestic life is already happening. Digital assistants like Amazon Echo and Alexa allow for voice-activated control of our smart home(dimming light, locking the door, etc at our command).
ML is being increasingly used in healthcare for faster patient diagnosis. ML programs can predict health problems based on age, socioeconomic status, and genetic history which helps prevent illness. Hospitals are currently using ML for accurately detecting tumors in radiology scans and detecting cancer. Computers can use large data sets and an algorithm to classify the images from scans. ML algorithm has been written that can detect cancer more accurately than the best pathologist, freeing doctors up to make the treatment decision more accurately and quickly.
Fully automatic driverless cars are the most prominent display of ML technology. Driverless cars can differentiate between trees and pedestrians, fields and roads, and many road signals, which has opened a lot of opportunities in goods delivery and personal transportation. The technology used here is image recognition and classification. Militaries all over the world are successfully using drone programs. Robots and drones are used to defuse bombs. Driverless trucks in mining pits which can be operated remotely from a distant control center.
Machine learning is the future of every business.
“Ten years ago, we struggled to find 10 machine learning-based business applications. Now we struggle to find 10 that don’t use it, “Alexander Linden, research vice president at Gartner.
Machine learning enables an analysis of a massive quantity of data and can provide a faster and more accurate result that can help in identifying profitable opportunities and dangerous risks. A few of its applications in business are:
The broad implication for all kinds of data entry and classification tasks that previously required human intervention can now be done by machines.
Ecological experts are using machine learning and AI-enabled sensors to analyze data from thousands of sources to make accurate pollution and weather forecast.
Machine learning can provide a warning about system failure so that backup or restoration plans can be done on time. This reduces business downtime.
ML helps to predict demand better and can be cutting-edge technology for supply change management.
It helps in accurate market segregation and plans marketing strategies accordingly this surely improves ROI on marketing budget.
The banking and finance industry heavily relies on ML for things like customer service, fraud protection, investment and more.
With every discovery and step forward comes a range of both technological and moral implications of those innovations. Although ML helps humanity, this innovation can impact our normal lives when it begins to make a decision that has a personal impact on us. ML can take up most of our jobs and there can be an increased data privacy issue. We as a modern society will operate and function similar to open source.