Why is machine learning the future?

Source: Artificial Intelligence on Medium

Why is machine learning the future?

Arthur Samuel, A pioneer from the united states of America related in the field of artificial intelligence and computer gaming introduced the term “Machine learning” in 1959 while working in a period of time at IBM.

Machine learning is not something new which is found recently. It is present long days ago from the beginning of statistic days. In those days it was called statistical learning where the whole data is gathered from the science of learning from large historical data.

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Machine learning concept is here to stay for a long period of time, It can be used in predictive analysis, speech recognition, image recognition, pattern recognition, the scope of machine learning keeps on increasing.

Machine learning is important and stands in front of technologies from different other sectors from analysis to data management, from automation to speech recognition. Every industry will use machine learning in order to avoid errors, consume less time, easy of work for the employees and work more efficiently.

It is used in medical diagnoses like wearable sensors, medical and healthcare support, stock market predictions, Theft and malware predictions that are coming through emails, messages, etc.

The Importance Of Machine Learning

Machine learning has important business applications that drive the kind of real business results. Machine learning is performed through virtual Assistant solutions it automates tasks that would replace a living agent in the workplace. Machine learning has made periodic changes and a lot of improvements in the past few years, but still very far away from human performance as many times the machine needs the assistance to complete the task. We have influenced and positioned virtual assistant solutions which given seamless results compared to human intelligence in delivering the highest level of accuracy and understanding.

Data plays a major role in the system. It is the lifeblood of all the business. Data decision has driven decisions increasingly make the difference. Machine learning is the key to unlocking the value of customer data and corporate.

Machine learning has applications in almost all industries including manufacturing, retail, travel, hospital, healthcare, life Sciences, financial services and energy, feedstock and utilities, etc.

Manufacturing: Maintainance of predictiveness and condition monitoring of the system.

Retail: Selling and cross-channel marketing in the business.

Healthcare and life sciences: Identification of disease and risk satisfaction.

Travel and hospitality: Pricing dynamically.

Financial Services: Regulation and risk analytics.

Energy: Supply optimization and energy demand.

Dark sides of a career in AI/machine learning?

Machine learning has its own flaws because of its heavy and expertise and not a manpower job like software engineering there are a lot of new problems for the new people who are just going to begin or move into this field for the first time.

There is a high level of error with machine language interface, errors are problematic in the machine language due to the independent nature and autonomous nature of this technology. You run a machine language program because you don’t want a human to babysit the project.

Learn For More Information Artificial intelligence vs Machine Learning

In machine learning, results take time as a tremendous and big amount of work is done, especially if you have limited computing power, which can be potentially so costly. It also requires heavy data with unbiased and of good quality.

Machine Learning needs more time to let the Logarithms learn and develop their purpose with ease and accuracy, It also requires additional resources to function which can be additional requirements of computer power for you. Accurate and interpret results generated by the Algorithms is also a major challenge.

Machine learning being autonomous but more susceptible to errors, Care must be taken to prevent errors and omissions at the required period of time.

Conclusion:

Machine learning is advanced to better and is getting more power in the future due to technological advancements. With a few minor consequences, it can be neglected because the future entirely depends on the virtual conception. The development of machine learning just begun and there is more to go for future amendments.

As a result we studied the future of Machine Learning along with algorithms of machine learning applications which will help you to deal with real life.

We studied both adavantages and disadvantages of machine learning and their future requirements, developments, etc. Machine can be incredibly powerful when used in the right ways and in the right places where the bulk amount of data sets are present.

Since Machine learning is a big task it takes time to master it. We have to be good at both math and data analysis which is a required category to focus more. It depends on the individual how much passionate about learning this machine learning Course.

Hence it is clear that machine learning is the future and has a very good scope to build a career in it.