You hear people talking about machine learning. But are you sure what is the truth and what’s a myth? People are curious to know about machine learning and artificial intelligence but face a lot of confusions while getting started.
Machine learning was first used by multinational organizations such as Facebook, Google, and Amazon. Google used it for advertisement placement while Facebook used Machine learning for showing the post feeds. However, there are a lot of myths about machine learning and its impact. Let’s get started with a few of them.
1. Machine Learning Can Be Used Anywhere
This is one common myth that machine learning can be used anywhere. Nobody will spend Rs. 1,000 on the work worth Rs. 200 rupees. Machine learning is used only if you have Big Data sets. It is not worth to use machine learning for small data solutions as that can be done by a human effortlessly.
2. There’s No Difference Between Artificial Intelligence And Machine Learning
Most often we use machine learning and artificial intelligence terms interchangeably. However, both are not the same and not synonymous with each other. Robotics, computer vision, and natural language processes are areas under the artificial intelligence stream. Machine learning is learning about patterns, using statistics and data predictions.
3. Deep Learning Is A Machine Learning
Today, deep learning is a widely used term in the market. People are assuming that it is the ultimate solution for data science and machine learning problem. Deep learning is one of the complex and challenging concepts in machine learning. Deep learning is a subset of machine learning with multi-layer neural networks computation.
4. Machine Learning Platform Is Easy To Build, And Anyone Can Do It
Many people think that you can just Google about machine learning and easily build any platform. However, machine learning is a special technique that demands the expertise skill set. To learn machine learning, you should know how to prepare the data for testing and training, how to demarcate data, how to build an exact algorithm and very important, you should know about the productive system. To get expertise in machine learning, one should have hands-on experience with machine learning patterns and algorithms.
5. Machine Learning Can Work Independently Without Human Intervention
People have a belief that the machine learns the system without real programming codes. However, the algorithms for machine learning solutions are developed by humans. So human intervention is a mandatory part of machine learning; it can’t be ruled out entirely.
6. Machine Learning Is The Same As Data Mining
Data mining is nothing but identifying the unknown patterns and properties of data. On the other side, machine learning is to use existing patterns and properties for developing a solution. There is a fine line between data mining and machine learning.
7. Machine Learning Is The Future
In the future, no doubt machine learning can be used widely, but this is not the only future. There are more advanced technologies in the market that can be one step above machine learning. Self-driven car or robots have just been an imagination a few years back. However today it is a reality.
8. Machine Learning Will Take Over Human Work
It is one of the major fears that machine learning will replace humans. Though machine learning will automate the system and perform social activities to some extent, it will also create new job roles or develop a need for a new skill set. Machine learning will create more significant opportunities for new skills and creative thinking.
9. Machine Learning Is Prone To Failure
Machine learning works on the algorithms; so the success of a solution mainly depends on the algorithm. A successful machine learning solution requires the right algorithm. Every problem and situation demands different solutions. Therefore, the wrong algorithm leads to failure of the entire solution. You should have a clear plan for the algorithm.
10. Machine Learning Is Not Useful In Relationships
People believe that machine learning is useful only for identifying correlations, not relationships. Machine learning algorithms can be used for discovering relationships as well as recognize knowledge. Machine learning can read entire data and derive the links based on past data.
Recently, machine learning underwent many modifications and is now an important topic for debate. Since it will play a pivotal role in the future, it is better to clear certain misconceptions and myths about machine learning before getting started.