How Artificial Intelligence and ML can win Elections

No matter what industry your business or company is in, automation improves processes, eliminates a lot of paper, errors, and wasted time.Don’t make the simple mistake of thinking that business process automation is only for large enterprises!

Smaller businesses can definitely benefit from countless types of business automation.

If you truly want to become efficient, automation is something you will have to consider.

Savings in terms of time and resources add up significantly over the course of a year.

Think about how much money you spend on paper, ink, and envelopes, and an employee’s time spent on this particular activity in a given year.3.

That means no steps are inadvertently omitted or forgotten, nobody can cut corners, and you can expect the results of a process to meet standards every single time.

Deep learning is a subset of machine learning and which in turn is a subset of artificial intelligence.

Artificial intelligence is a process of teaching a computer to work as a human, machine learning is a technique to apply AI through algorithms trained using data and Deep learning is a type of machine learning inspired by the structure of the human brain.Look into: https://www.globalvoxinc.com/deep-learning/

We are in the crawling stage when it comes to applying machine learning.”- - Dave WatersTechnologies and their interdependencies are paving the way to a future that is smarter and intelligent to fulfill the demand for resources.

Cloud providers like AWS, Google and Microsoft offer Cloud with ML capabilities that require scads of processing power.

Undermentioned are a few applications of Machine Learning Algorithms using the Cloud Cognitive Cloud - There are millions of people using cloud and they produce massive amounts of data frequently.

The pre-existing unstructured datasets act as a source of information for the machines to learn from and adversely the cloud provides applications with sensory capabilities that are used to perform cognitive functions and make prospective decisions.

Chatbots providing solutions through chat has brought them into focus in the customer service industry eliminating human interaction, hence reducing any errors.

IoT Cloud - Gartner predicts that by 2022, more than 80 percent of enterprise IoT projects will include an AI component, up from only 10 percent today.

Like every other industry, data has also been the core of the insurance industry.

Over the due course of time, what actually has changed is the amount of data and the speed at which machines are processing it for driving useful insights.

Data-driven insights play a vital role in boosting this industry by making decisions based on facts, figures, and user patterns.

Insurance providers adopt Artificial Intelligence (AI) & Machine Learning (ML) technologies to enhance the end-user experience, develop improved solutions for increasing operational efficiency, and build accurate underwriting models.Machine Learning is an application of Artificial Intelligence technology that allows computer systems to deploy algorithms for learning and improving my experience.

Such algorithms are used for building mathematical models which can be used as training data, allowing systems to make decisions & predictions.AI & ML in Insurance IndustryAI and ML technologies make it easier for insurance providers to use the data at their desired pace and way.

Many organizations in this industry have access to data that is usually structured and stored in databases.