Deep Learning Versus Machine Learning

Deep Learning and Machine Learning are two terms that are in buzz these days. However, the two terms are often misunderstood by many people as they consider both are same. But they are not. Both of them are different terms. Let’s understand these two terms.

Machine Learning:

Machine Learning uses the set of algorithms that are used to parse the data and make informed decisions based on what has been learned.

Deep Learning:

In Deep Learning, the set of algorithms are able to determine on their own whether a prediction is accurate or not. The model does computing on its own by continuously analyzing the data with a logical structure.

Deep Learning can be considered as a subset of Machine Learning as deep learning utilizes the set of algorithms by learning from real-time problems and then building a hierarchy of concepts to make intelligent decisions.

Let’ understand the two with the help of an example. There is an application in your smartphone that triggers when someone says the word, ‘open the phone’. Once this is said, the phone unlocks and then you can perform the desired operation. Now, if deep learning model is integrated with the system then the system would be able to unlock the phone using different phrases like ‘I want to access my phone.’ Or ‘I want to fetch some data from my phone’ etc.

The trend toward Deep Learning

The innovation in technology and the wider computing capabilities has resulted in the development of Artificial Intelligence. Artificial Intelligence technology can learn and make decisions on its own. The recent developments involve the recognition of the new strains of malware that has the capability to give improved security and tighter defenses in the future.

The Anti Virus development companies even claim the development of deep learning capabilities has the potential of enhancing their capability to detect 20% more malware in comparison to the existing technology. Such advancement effectively utilizes key technologies including Big Data Analytics, Deep Learning, Knowledge Management, with efficient utilization of system machinery along with the judgment of the user behavior.

Conclusion

In conclusion, Deep Learning has a wider potential in the future. The technology is expected to grow more complex and offer simplified solutions using the big data platform and the other proliferating technologies of the present world. It is expected that the deep learning tools would be embedded in every design surface in the coming days. Driving, Search, Predictive Analytics domain, Anti Virus companies, and many others are soon going to expect a major transformation with the enhancement of Deep Learning technology. It will deliver faster value to users by simplifying the day-to-day tasks.