Machine Learning

Machine Learning

1. What is it

   • Machine learning is the use of artificial intelligence (AI) that gives systems the ability to learn and improve the experience without being explicitly programmed.
   • Machine learning focuses on the development of computer programs that can access data and use learn for themselves.

2. Where is it used

   • The machine learning is one of the most popular applications of AI in which computers, software, and devices. It performs via recognition, it is like a human brain.

3. Disadvantages

   • Machine Learning requires massive data sets to train on.
   • There can also be times where they must wait for new data to be generated.
   • ML needs enough time to let the algorithms learn enough to fulfil their purpose.
   • It also needs massive resources to function.
   • The challenge of accurately interpret results generated by the algorithms.
   • It can set off a chain of errors that can go undetected for long periods of time.
   • Machine Learning is autonomous but highly susceptible to errors.

4. Advantges

   • It is used in so many industries of applications such as banking and financial sector, healthcare, retail, publishing, and social media,
   • · It is used by Google and Facebook to push relevant advertisements based on users search history.
   • It allows time cycle reduction and efficient utilization of resources.
   • Due to machine learning there are tools available to provide continuous quality improvement in large and complex process environments.