Creativity to make our surrounding automatic is our one and only aim left. Day by Day AI and Machine Learning automating more and more parts of our life.
We all have heard about AI thanks to movies for its introduction, but what about Machine Learning/ML. ML is the buzzword for most of us. Basically, ML makes computer to learn.
In a nut shell, ML is similar to our very first learning part of our childhood. We have a book containing a lot of pictures of fruits, animals, vegetables, and trees. These are teaching data set for any child. That data will be used to answer a question.For example, a picture is given to a child and he/she has to identify that pictures based on pictures saved in his/her mind. It is what the ML. ML continues to update its teaching data set based on correctly or incorrectly credits:http://www.parlezwireless.com/
identification of things and get smarter and intelligent at completing its tasks over time. If you have used Google, Netflix, Amazon, Gmail, then you have interacted with machine learning (ML).
I am sure about recommendation type of thing if we use services like YouTube, Amazon or Netflix. Every click being monitored and recorded. Driven by Intelligent machine learning, these sites analyze our activity and compare it to the millions of other users to “recommend” or “suggest” other similar videos, products or films that we might like.
- Online Search
AI is transforming Google and other search engine results by watching our response to result display. We click the results show on the very first page and we are done because we found what we are looking for. If not, then we go to the second page or refine our query at this point we assume that search engine didn’t understand what we want, so it learns its mistake and shows the better result in the near future.
- In Hospitals
Due to its nature of analyzing vast amounts of data, ML takes the first place to process information and spot more pattern like cancer or eye diseases than a human can by several orders of magnitude.Computer-aided diagnosis (CAD) can help radiologists find early-stage breast cancers that might otherwise be missed, and it can identify 52% of these missed cancers roughly a year before they were actually detected. Zebra Medical Systems is an Israeli company that applies advanced machine learning techniques to the field of radiology. It has amassed a huge training set of medical images along with categorization technology that will allow computers to predict multiple diseases with better-than-human accuracy. In 2016, the company unveiled two new software algorithms to help predict, and even prevent, cardiovascular events such as heart attacks.
- Data Security
According to Kaspersky, between January and September, 2016 ransomware attacks on business increased from once every 2 minutes to once every 40 seconds. Symantec also reported high levels of ransomware attacks, over 50,000 in March 2016 alone. A report by Osterman Research indicates 47% of organizations in the US in 2016 had been targeted at least once. A survey in the UK suggested 54% of businesses had been attacked at least once. Friday, May 12, 2017, saw one of the largest most widespread attacks to date – the WannaCry ransomware. According to Deep Instinct new malware tends to have almost the same code as the previous one only 2 to 10% changes. Due to the slight change in code ML can predict which files are malware or not with great accuracy.
- Email spam filtering
According to Computer World magazine, the average employee gets 13 spam messages a day – and over 80 percent of all the email messages zipping around the Internet are spam. Microsoft founder Bill Gates is the most spammed man in the world, with 4m emails arriving in his inbox each day. All credit goes to ML which filter all emails and classify them into spam and not spam. credits:http://www.asistiletisim.com
- Marketing Personalization
Personalized marketing is the ultimate form of targeted marketing. To sell more we have to serve better and to serve better we have to understand customers. This is the base idea behind marketing personalization. Companies can personalize customer emails, which products will show up as recommended, offer they see, coupons and so on, these are just the tip of the iceberg. All above things are achieved by the advance ML algorithm.
- Fraud Detection
ML and AI are used and become better day by day at spotting potential cases of fraud or anomaly detection across many different fields. The Royal Bank of Scotland (RBS) for example, is using machine learning to fight money laundering. Companies have a lot of data and they use ML to compare millions of transactions and can precisely distinguish between legitimate and fraudulent transactions between buyers and sellers.
- Natural Language Processing (NLP)
Virtual personal assistants – likes of Siri, Alexa, Cortana and Google Assistant – are able to follow instructions because of voice recognition and it is NLP. NLP process human speech and match it to best-desired command and respond it in a natural way.
- Financial Trading
At its heart, Financial trading is no different to any other form of trading: it is about buying and selling in the hope of making a profit. Here comes its beauty “Predict what the stock market will do on any given day”. Again ML wins the game of prediction with a very close margin. ML helps many prestigious trading firms to execute trades at very high-speed and high volume for prediction. ML throws human out of a window in consuming the vast amount of data at a very fast pace.
- Smart Cars
Of all the uses for machine learning, one of the most exciting ones i.e Smart Cars. A recent IBM survey of top auto executives saw some 74% of these stating they expected credits:http://ichef.bbci.co.uk
there would be smart cars on the roads by 2025.Smart cars are integrated with IoT, ML and AI which help car to do many fantastic things by own like learn their owners and environment, adjust internal settings, report and even fix problem, offer real time advice about traffic and road conditions and in extreme cases it may even take evasive action to avoid a potential collision.