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Difficulties in Adapting Machine Learning By Daniel Irwin

  in Education | Published 2018-09-05 07:40:23 | 35 Reads | Unrated

Summary

As Artificial Intelligence spreading in every industry, it’s important for your business to adopt the same to stay competitive in the industry.

Full Content

Machine Learning is one of the trending topics in today’s digital world. It is a type of Artificial Intelligence (AI) in which the software gives you the ability to learn based on data. For instance, you must have noticed how YouTube, Amazon and many other online platforms recommend similar products or videos you should check out. Those recommendations are based on your previous actions. Nowadays, everyone is looking to incorporate machine learning into their business.

The services generated throug

h Artificial Intelligence or machine learning may seem magical, but reaching to that point involves a lot of work and numerous challenges.

1. Requires Quality Data: The machine learning completely depends upon the input provided to it. Data plays the crucial part of machine learning, the machine will learn what has given to it. The data decides how the machine will evolve and what value can be added to your product/project by utilizing machine learning. For instance, on images it scans has small cars, you will not get the accurate results. To achieve success, you need quality images. The machine’s ability to grasp directly depends on the quality of the data it encounters.

2. The Quantity of Data: Not only quality data, but to achieve the expected outcome you need data in high quantities. If you are providing a machine with limited data for hundreds of users per month, the machine won't have enough information to deliver the same service to thousands of users per months. Its sample might be too small to be accurate.

3. Requires Continuous Testing: Having quality data in sufficient quantity is not enough. Instead, you need to keep testing the data at regular intervals. The machine might learn techniques on its own, but the learning is based on how the machine was designed and the data it’s being fed.

4. It’s Expensive: Machine learning can’t be cheap. So while designing a machine for any of your product/project, keep your budget in your mind. Machine learning experts are high is demand and charge high for their work as there is a lot of effort involved to figure out the best designing and creating the models, offering training to meet expectation, testing them on, etc.

The machine learning is not a magic, it needs lots of efforts and dedication to design a perfect model that will suit your requirements. As Artificial Intelligence spreading in every industry, it’s important for your business to adopt the same to stay competitive in the industry. There are various courses that may help your team to learn Artificial Intelligence, including Data Science with R, Data Science with Python, machine learning, Big Data and Hadoop, Apache Cassandra and many others. Keep all the points in mind before initializing your AI model.​

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