Advantages and disadvantages of machine learning

We keep hearing the term machine learning not only does it offer growth in career but also it promises to solve problems and also benefits the business organization. It makes predictions and helping them to make a better decision amidst all hype around the Big Data. Let us check out the advantages and disadvantages of machine learning to know more about it.

Advantages or Pros of machine learning: 

  1. Machine learning will study vast quantities of data and discover complex trends and patterns that may not be evident to humans. For example like E-commerce website like Amazon, it serves to understand the browsing behaviour and purchase history of the users to understand consumer behaviour. It is very useful to reveal a relevant advertisement to them.
  2. You don’t need any human intervention to observe your project every step of the way. Since machine learning gives machines the ability to learn, lets them make predictions and also improve the algorithms on their own. In addition, ML is also good at recognizing spam.
  3. Machine learning algorithms are good at managing multi-dimensional and multi-variety data.
  4. Keep improving in accuracy and efficiency as the ML algorithm gains experience. This characteristic makes them make better decisions.
  5. Machine learning is used in almost every industry from defence to education. Many businesses gain advantages to generate profits, cut costs, automate, predict the future, analyze trends and pattern from past data etc. ML applications, such as GPS traffic tracking systems, e-mail spam screening, text prediction, spell check and correction. ML is a branch of artificial intelligence. For more details, you can also check out the advantages and disadvantages of artificial intelligence.

Disadvantages or Cons of Machine Learning: 

  1. One of the main disadvantages in the field of data science and machine learning is the acquisition of data.
  2. Being easy to automate processes using machine learning, it sometimes happens that data in between is improper. This might cause incorrect results of errors. The one important characteristics always remember about this technology is Garbage In Garbage Out.
  3. Another big problem is the ability to correctly analyze algorithm-generated data. For this reason, you must also carefully select the algorithms.
  4. Machine Learning is autonomous but somewhat error-prone. Suppose you train a data set algorithm that is minimal enough not to be inclusive. You wind up with bias forecasts resulting from a bias preparation package. This leads to meaningless commercials being presented to consumers.
  5. Machine Learning algorithms are capable of handling large volumes of data. There is also an improvement in the amount of data, the time to learn from, and process data. Perhaps this may also mean extra capital for computation.

Explore more information:

  1. Advantages and disadvantages of Big Data
  2. What are the use and need for Big Data?
  3. What are the characteristics of Big Data?
  4. Benefits of using Big Data in the manufacturing industry
  5. What are the advantages of Big Data in accounting?
  6. What are the risks and challenges of Big Data?
  7. What are the challenges of Big Data in healthcare?
  8. Types of Big Data
  9. Application of Big Data in the government sector
  10. Application of Big Data in E-commerce

Thank you for reading this article. If you have any queries or suggestions regarding this article on the advantages and disadvantages of machine learning then do comment in the comment section below.

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