How Machine Learning Applications have Redefined Our Daily Activities?
Do you know what machine learning is? It is a subset of artificial intelligence that emphasized using statistical techniques to fabricate intelligent computer systems to learn from databases. Machine learning and Data Science application are counted as one of the most interesting innovations, since the microchip. Artificial Intelligence (AI) is used today as a fanciful concept from science fiction, but becoming a daily reality. Machine learning has helped us enhance the industries, professionals, and everyday living.
Technology is advancing constantly, thus, revolutionizing every facet of our habit. Voice-controlled personal assistants — Amazon’s Echo and Alexa — were the first brush-up of humans with Machine Learning. These devices are transforming as the new normal, due to the increasing demand for smart homes.
The intelligent systems built on machine learning algorithms that can learn from historical data and experience. It has helped us spend more productive, happier and healthier lives. AI is popularly known as the industrial revolution. This new revolution will harness cognitive ability and mental growth. According to experts, the one-day computer will not only replace manual labor but also take over mental labor. Globally millions are being spent by several sectors in applications and innovations.
“$2.9 trillion would be spent on new business and value opportunities in AI by 2021,” says Gartner. The firm has also forecasted 6.2 billion hours of worker productivity attributable to AI. The way technologies have been looked or used had changed. According to Elon Musk, “Most people don’t understand just how quickly machine intelligence is advancing; it’s much faster than almost anyone realized, even within Silicon Valley.”
Technology with super-human abilities is affecting businesses and industries, indeed, offloading the pressure of work from humans.
Here is a list of activities that have witnessed the influence of machine learning:
First, one of the most common usages of machine learning is image recognition. There are various situations, where you can distinguish the object as a digital image. For instance, in the case of a black and white picture, the intensity of each pixel is served as one of the measurement. However, the colored images are measured in 3 three different colors – green, blue and red.
When it comes to face detection in an image, machine learning is the key. This technology is used for the recognition of characters to differentiate handwritten as well as printed letters. You can fragment a piece of writing into smaller images, each comprising a single character.
Improve Health Care
“2018 will be the year AI becomes real for medicine. … In 2018, we’ll begin the adoption of a technology that may truly transform the way providers work, and the way patients experience healthcare, on a global scale.” — Mark Michalski, executive director, Massachusetts General Hospital.
Soon hospitals may take support from AI to acquire health care to another level. It has been analyzed that hospitals that deepened on machine learning to aid patients have a better treatment graph. AI is also tracking some of medicine’s most obdurate problems. In addition to this, allowing researchers to understand genetic disease with the help of predictive models.
With the change in technology, professionals use high-performance computing GPUs to render effective medical care and services. It has enabled doctors to medical aid for complex and rare health problems.
Deep learning models offer real-time insights and combine them with the sudden increase in computing power. This helps experts to diagnose patients with accurate results. Also, develop effective new treatments and drugs, calculate adverse reactions, eradicate medical and diagnostic inaccuracy, and reduce the prices of drugs and services for patients.
Things don’t end here!
For instance, performing everyday tasks can be a challenge for an array of grey-haired people. There are various individuals, who take the help of human robots (AI) and offer them extensive care. This has not only made seniors’ life comfortable and easy but also solved the eldercare problem for many families. This human like machine allows seniors to spend an independent and easy life.
Banking – Innovation is the new Black!
Can you calculate the number of bank accounts? Did you know the number of credit cards used in circulation? The banking sector has witnessed a dramatic change due to the birth of AI.
Using purchase patterns and locations, AI can also help credit issuers and banks resolve fraudulent activities.
This technology is based on anomaly detection models to monitor transaction requests. On a general note, spot patterns in your transactions and alert users about suspicious activity.
Online Fraud Detection is one of the major challenges faced by the financial sector. Machine learning has been providing potential solutions to make cyberspace a safe and secure place. Moreover, tracking online monetary fraud is now an easy and feasible task.
For instance, Paypal is currently using ML for protection against money laundering. The company is taking the help of several tools that help them to compare a ton of transactions taking place between the buyers and sellers.
Machine Learning Use in Security
Machine learning algorithms have the power to help businesses detect malicious activity in a shorter time and control attacks before they begin.
David Palmer – UK based start-up owner says, “Darktrace recently helped one casino in North America when its algorithms detected a data exfiltration attack that used a “connected fish tank as the entryway into the network.”
The cyber threat landscape forces organizations to constantly correlate and track millions of externals as well as internal data points across their infrastructures and users. Machine learning has resulted in reducing the pressure of cyber threats for companies. By automating the analysis, the cyber team can easily detect threats and isolate situations that require detailed analysis.
Learning association is the way of developing insights into several associations between the products. One perfect example to explain this is, unrelated products can be associated with one another.
In addition to this, if you buy a product, the website will show similar products as an option to buy.
Refining Google Search
Do you know Google and various other search engines use machine learning to boost the search results for users?
Every time a user executes a search, the algorithms at the backend keep a watch on how you respond to the results. If you open the first results and stay on the web page for a long duration, the search engine presumes that the results it displayed were in accord with the inquiry. Moreover, if you reach the second or third page of the search consequences, but do not unlock any of the results, the search engine estimations that the outcome served did not justify the requirement. Thus, the algorithms working at the backend improvise the search outcomes.
The spectacular change in technology has created better and promising opportunities for machine learning jobs as well.
Email clients use several spam filtering approaches. To make sure that these spam filters are been timely updated, they are power-driven by the machine learning algorithm.
When rule-centric spam filtering is performed, it is unable to track the latest tricks adopted by spammers. C 4.5 Decision Tree Induction, Multi-Layer Perceptron and many more, are some of the spam filtering techniques that are empowered by ML.
Over 325, 000 malware are distinguished each day and each piece of code is 90–98% compared to its prior versions. The system security programs are empowered by machine learning, understanding the coding pattern is important. Indeed, they identify new malware with a 2–10% variation effortlessly and protect against them.
Use in Sales and Marketing
If you have ever used an app to book a cab, you are already using Machine Learning. It offers a customized application that is exclusive to you. Automatically perceives your location and provides options to either go home, office, or any other commonplace, based on your Patterns and History.
It utilizes a Machine Learning Algorithm layered on top of Historic Trip Data to create a more accurate ETA forecast. With the completion of Machine Learning, they saw a 26% precision in Pickup and Delivery.
Just think about your online shopping experience, you check an item on Amazon, but you do not buy it at that time. And, some other day, you are surfing the internet and suddenly you see an ad for the same product. Wondering how does this happen?
Well, this happens because Google tracks your search history, and ads are recommended on the base of the search engine. This is one of the most amazing features of Machine learning. There are some more features, including complimentary purchase suggestions, product recommendations, and customized shopping.
Amazon’s transactional A.I. has resulted in making gigantic monetary gains online. Its machine learning algorithms have analyzed the behavior of users online and has received smart and accurate overtime in predictive selling.
Do you know that 35% of Amazon’s revenue is generated by Product Recommendations? Yes, you read this right!
Virtual Personal Assistants
Alex, Cortana, and Siri – digital assistants – are gradually turning out to be a household name. There are several platforms such as iOS, Windows and Android mobile phones. These are quite useful in exploring information about everything available on the web, from weather prediction to online shopping.
Digital assistants are been designed to make our lives easy. In addition to this, this application help in setting reminders, host other function and maintaining personal schedules.
Self Driving Cars
One of the most innovative and amazing applications of Machine Learning algorithm is self-driving cars. It is has taken over the nerves of the people and changed the way of driving for many. The current Artificial Intelligence is driven by hardware manufacturer NVIDIA, which is based on the Unsupervised Learning Algorithm.
Well, the incorporation of sensor date processing in an ECU in a car, it is important to improve the utilization of machine learning to accomplish new jobs. The potential applications involve evaluation of driving scenario classification through data fusion from several external and internal sensors, such as radar, cameras or the Internet of Things.
Are you one of those, who love to travel, but find difficulty in communicating with the locals or find local areas? Google translator comes to rescue you!
Google’s GNMT (Google Neural Machine Translation) is a Neural Machine Learning designed to work on an array of dictionaries and languages, uses Natural Language Processing offers the accurate translation of any word or phrase.
Google translator is counted as a wonderful and most commonly used Applications of Machine Learning. It has certainly redefined linguistic rules for many. Now, language is no more a barrier to connect. Translator enables to read and understand different languages in the most sorted manner.
As all the sectors have witnessed a gigantic impact on machine learning, indeed, the demand for machine learning courses has also increased. Moreover, several educational platforms offer online courses to learners.
Online Video Streaming
The experience of watching online movies or online entertainment has taken a new turn. Netflix has transformed into a game-changer in the entertainment world. This platform has above 100 million subscribers; it comes as a no-brainer that Netflix is a colossal name in the online streaming world. The protagonistic character behind the success of this online entertainment platform is Machine Learning.
Its algorithm continuously gathers enormous amounts of data about activities of users such as pause, rewind or fast forward, the record the time duration you watch content, connecting back with the content watched, and scrolling and browsing behavior.
The algorithm collects the data for each subscriber; they use their recommender system and a lot of Machine Learning Applications. That is why they have such an enormous customer retention rate. Thus, this technology has also resulted in improving the user experience. In a nutshell, it would not be wrong to say, that machine learning is an unbelievable solution in the field of artificial intelligence.
And, several machine learning techniques have some fear-provoking allegations; these applications are ways through and can improvise the way of living for users.
Machine learning gets to detect disease, better business decisions, boost productivity, predict the weather, and perform a plethora of things. With the accumulation of growth in technology, we require as well as demand better tools to understand the data.
Do you know that Python has a gigantic collection of libraries for machine learning purposes? Thus, machine learning by python also serves as a great asset to the tech world.