• Sanjay Kumar

What is Deep Learning

Updated: Sep 20

Many people often confuse machine learning with deep learning. Let’s discuss in brief about “Machine Learning Vs. Deep Learning”. Machine learning is a broad concept and a part of AI, which focuses on making machines able to collect and learn from the collected data.


Deep learning is a part of machine learning that focuses on teaching machines to act naturally like human beings. It utilizes neural network to go through a huge volume of data and its algorithm is inspired by human brain.


Like human beings do task repeatedly and make improvements overtime, machines with deep learning algorithm do the same as well. The deep learning AI algorithm uses neural network to dig deep and learn things to solve problems.


However, the deep learning algorithm demands a huge volume of data to be able to perform efficiently. Furthermore, it also requires a higher computation power to carry out sophisticated processes of deep learning.


In the beginning, we need to feed input (data) to the machine. After that, we compare the output generated by the system with the output of the dataset. It is obvious that the output generated by the machine will be wrong due to an untrained algorithm.


Now, we will show the system what went wrong with its processes to train the algorithm to produce improved results in the future.


There are many corporations and small businesses who are investing in deep learning.The world has got many improved technologies, thanks to deep learning. The number of virtual assistants are increasing at a rapid rate along with its effectiveness. The virtual assistants use deep learning algorithms to understand human speech and interact with the users.

If you are working in global organizations with a lot of diversity, the system with deep learning helps in the translation service. It can quickly translate different languages to enhance productivity. These devices can be helpful for travelers, businesses, and government institutions.


There are many other applications of deep learning, such as self-driving cars, chatbots, facial recognition, image colorization, and so on.


The deep learning technology is improving a lot. Now the question is how far can it go. The pace at which deep learning research is moving forward is insane. There is a mobile app, Arxiv, that keeps track of all the deep learning milestones.


Currently, the professionals use the mix of tools for carrying out deep learning operations. However, we might see the standardization of tools. To overcome the confusion, they could create a set of standard tools that will make tasks easier for them.


We can also see easier programming frameworks for accelerating deep learning progress in the future. What this means is that it will be easier to create deep learning codes, which will foster innovation. In early days of programming, the programmers needed to use machine level codes. However, it has evolved a lot since then. Similar progress will happen in deep learning as well.


Be expected to see more advanced deep learning tools in the future. With that said, the deep learning will not only be limited to huge corporations. We can expect the price of technology to go down as the time progresses. Google recently announced that it will make machine learning accessible to all.


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