Advantages and Disadvantages of Machine Learning in 2020

Machine Learning advantages and disadvantagesMachine Learning is a technology that has witnessed an exponential rise in its usage and popularity in the last couple of years. A huge number of aspirants from around the world are quickly learning this technology and putting the knowledge to various use. Machine Learning Engineers are in high demand as a result. While there are several evident pros, it does come with some cons. In this article, we are going to share some advantages and disadvantages of Machine Learning.

Advantages of Machine Learning

Machine Learning Advantages

Continuous Improvement

Machine Learning algorithms are capable of learning from the data we provide. As new data is provided, the model’s accuracy and efficiency to make decisions improve with subsequent training. Giants like Amazon, Walmart, etc collect a huge volume of new data every day. The accuracy of finding associated products or recommendation engine improves with this huge amount of training data available.

Automation for everything

A very powerful utility of Machine Learning is its ability to automate various decision-making tasks. This frees up a lot of time for developers to use their time to more productive use. For example, some common use we see in our daily life is social media sentiment analysis and chatbots. The moment a negative tweet is made related to a product or service of a Company, a chatbot instantly replies as first-level customer support. Machine Learning is changing the world with its automation for almost everything we can think of.

Trends and patterns identification

This advantage is a no brainer. All of us interested in Machine Learning technology are well aware of how the various Supervised, Unsupervised and Reinforced learning algorithms can be used for various classification and regression problems. We identify various trends and patterns with a huge amount of data using this technology. For example, Amazon analyzes the buying patterns and search trends of its customers and predicts products for them using Machine Learning algorithms.

Wide range of applications

Machine Learning is used in every industry these days, for example from Defence to Education. Companies generate profits, cut costs, automate, predict the future, analyze trends and patterns from the past data, and many more. Applications like GPS Tracking for traffic, Email spam filtering, text prediction, spell check and correction, etc are a few used widely these days. Machine Learning is a branch of Artificial Intelligence, the latest trends and applications can be found in Artificial Intelligence Trends in 2020.

Disadvantages of Machine Learning

Disadvantages of Machine Learning

Data Acquisition

One of the most painful points in the field of Data Science and Machine Learning is the acquisition of data. Additionally, collecting data comes with a cost. Also, it so happens that when we are collecting data from surveys, it might contain a large volume of bogus and incorrect data. Many times we do face a situation where we find an imbalance in data which leads to poor accuracy of models. These reasons make data acquisition a massive disadvantage.

Highly error-prone

“Garbage In Garbage Out” is the thing to always remember in this technology. The data we push in the models as training data must be clean and accurate for the problem we are solving. Being easy to automate processes using Machine Learning, it sometimes does happen that data in between is improper. This might cause incorrect results or errors. For example, we might witness a situation where customers may be classified as defaulters or customers are recommended products not related to their search history or patterns.

Algorithm Selection

A Machine Learning problem can implement various algorithms to find a solution. It is a manual and tedious task to run models with different algorithms and identify the most accurate algorithm based on the results. This is a disadvantage.

Time-consuming

Machine Learning models are capable of processing huge amounts of data. Larger the volume of data, the time to learn from data and process it also increases. Sometimes it might also mean additional resources for computing.

Conclusion

Machine Learning advantages and disadvantages as mentioned above will help the reader know a bit more about this technology. Falling under the umbrella of Data Science, one can know more about data Science in A Beginner’s guide to Data Science. We at Ivy Professional School have got industry-relevant courses on Machine Learning using Python. Visit us at www.ivyproschool.com or call us on 7676882222

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