Machine Learning

Despite acknowledging the value of AI and machine learning technologies most business organizations are lagging behind in using them reports a survey from RELX Group.

More than 91 percent of senior executives polled understood that AI and machine learning were important but only 56 percent were using them and 18 percent could not say how the technologies were being used in their business.

RELX says the gap in adoption is due to senior leadership not being able to communicate the benefits of the technologies to employees and how or why they are being used.

"While awareness of these technologies and their benefits is higher than ever before, endorsement from key decision makers has not been enough to spark matching levels of adoption." said Kumsal Bayazit, Chair of RELX Group's Technology Forum.

"Acknowledging that the world is changing needs to be coupled with significant investment and focus on these emerging technologies to stay competitive in today's business landscape."

The top uses for these technologies is to improve worker productivity (51 percent), to make better business decisions (41%), and to streamline business processes (39 percent).

Additional findings: Companies are saving money by automating decisions (40 percent), retaining customers longer (36 percent) and easier detection of fraud and waste (33 percent).

RELX recently opened an AI Lab in Amsterdam so that it's scientists can work with Dutch universities to combine developments in academia and from the industry. It recently published open access research on AI and machine learning as part of its free Artificial intelligence Resource Center.

RELX Group has a valuation of $41 billion. It used to be a major media company with hundreds of magazines and newspapers and was better known as Reed-Elsevier. It has successfully transitioned into an information and data company selling a variety of services to businesses and at a far higher valuation than if it had remained a media publisher.

Machine learning and artificial intelligence have created a buzz in the market with every industry looking a way to use them in their operations. They have already conquered various big industries and markets and are and will make our lives even better in the near future.

 1.Machine learning in Digital Marketing: -

 The use of machine learning and artificial intelligence in the digital marketing industry can be really useful and helpful to the marketers who will be able to process tons and tons of consumer data and analyse the best product, message and timings to showcase a particular product or service to the consumer so as to get a higher conversion rate.

Being able to recognize the consumer habits, preferences by analysing their online activity with the help of ML and AI down to individual consumers will have drastic improvements in the sales and the content engagement of the companies.

  1. Machine learning in Sales: -

There are tons of ways the companies can use machine learning in their sales process. Some of them are listed below: -

  1. Improve sales forecasting: - With the help of machine learning, companies can now compare and analyse previous customer sales pattern and data in an efficient manner which help sin better sales forecasting.
  2. Predict customer needs: - The major reason for the success of a company is to be able to successfully predict the needs of its customers at the right time and providing him with that result and product. This is the area where machine learning plays an important role. It stores the purchase data of the customers and analyses the data thoroughly in order to be able to predict the next demand of the customer before he searches for it.

 3.Machine learning in Healthcare: -

With the help of machine leaning the customer’s illness patterns and medications for the same can be tracked and memorized by the software which can provide the results as and when required. Quicker availability of medications will help to counter the disease better which will improve chances of saving more lives.

  1. Machine learning in e-learning: -

E-learning is an upcoming concept that has been using this technology for some time now and sees it as a future of the industry. The potential benefits are: -

  1. Personalized content- ML algorithms forecast the outcomes which allow the instructor to provide a more personalized e-learning content based on previous results and learning capabilities.
  2. Learning motivation- With the help of personalized content, now the learners are being able to learn at a personal level in accordance with their skill and mental level. This gives them a sense of understanding and a motivation to continue the learning process.

 Overall, Machine learning and artificial intelligence are set to perform wonders for the people which will make our lives easier and quicker. The system will be able to predict even the smallest of details and work in order to overcome the flaws.

 

 

Machine learning is a type of artificial intelligence (AI) that allows software applications to become more accurate in predicting outcomes without being explicitly programmed.The processes involved in machine learning are similar to that of data mining and predictive modeling.

Examples and real world use cases of machine learning: 

 

Financial Services:

Online Fraud Detection

Machine learning is already used by cyber security firms to protect enterprises from online frauds and money launderings.ML will help personal finance customers with right products to choose for their Insurance and fintech needs.

Customer satisfaction

Machine learning helps firms to track customer spending patterns and customer churn before they occur.They analyse the user activity and provide insights into the data.

Calculating risk.

Smart machines can analyse a large number of datasets (credit scores, spending patterns, finance data) to accurately assess risk in both insurance underwriting and loan assessments, tailoring them to a specific customer segmentation and profiles.

Social Media Services:

Social media networks are using machine learning to provide personalised news feeds, and ads targeting to right audience

Face recognition is one example ,If you upload a friend picture then facebook detects the friend picture and scan through unique features and your friends list and tags accordingly to match it.

Virtual personal assistants

A virtual assistant is a software agent that can perform tasks or services for an individual. Sometimes the term "chatbot" is used to refer to virtual assistants generally or specifically those accessed by online chat (or in some cases online chat programs that are for entertainment and not useful purposes).

Virtual Assistants are integrated to different platforms.

For example:

Smart Speakers:

Amazon Echo

Google Home Smartphones

Samsung Bixby on Samsung S8

Mobile Applications: Google Allo

There is many use cases and examples of Machine Learning exists and it is still evolving day by day,As we see now enough data is available with companies like

Amazon,Google and other big companies.

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