Advantages of Machine Learning

Easily identify trends and patterns

  • Machine Learning can review large volumes of data and discover specific trends and patterns that would not be apparent to humans.
  • For an e-commerce company like Flipkart or Amazon, it serves to understand the browsing behaviors and purchase histories of its users to help cater to the right products, deals, and reminders relevant to them.

No human intervention needed (automation)

  • Machine Learning does not require physical force i.e., no human intervention is needed.

Continuous Improvement

  • ML algorithms gain experience, they keep improving in accuracy and efficiency.
  • As the amount of data keeps growing, algorithms learn to make accurate predictions faster.

Handling multi-dimensional and multi-variety data

  • Machine Learning algorithms are good at handling data that are multi-dimensional and multi-variety, and they can do this in dynamic or uncertain environments.

Disadvantages of Machine Learning

Data Acquisition

  • Machine Learning requires massive datasets to train on, and these should be inclusive/unbiased, and of good quality.

Time and Resources

  • ML needs enough time to learn and develop enough, to fulfill its purpose with a considerable amount of accuracy and relevancy.
  • It also needs massive resources to function.

High error-susceptibility

  • Machine Learning is autonomous but highly susceptible to errors.
  • It takes time to recognize the source of the issue, and even longer to correct it.