REVOLUTIONARY TECHNOLOGICAL INTERACTION THROUGH ‘DEEP LEARNING’!

 

This era is a bundle of rapid advancements and widespread adoption by different sectors. When we compare the human brain with AI it becomes an enchanting and complex topic. Deep Learning is a subset of machine learning which is a subset of Artificial Intelligence. Artificial Intelligence lets the machine mimic human behaviors. 

Deep Learning is inspired by the structure of the human brain. It works through artificial neural networks with value-attached channels called weighted channels. What makes Deep Learning interesting is its ability to understand the features of the environment through its neural network without any human mediation. This feature of Deep Learning makes it better than machine learning which includes human mediation for the process of identification of a substance.

Advancements 

Horus Technology is now developing a device for blinds that lets the user understand the environment they are in through Deep Learning. This helps the users to understand how the environment they are in is with the vision of the computer.

Deep Learning [CNN(Convolutional Neural Networks)] is the reason behind image recognition and any spatially organized data. Many more researches taking place under Deep Learning. From the photos of our mobile phones categorizing the images based on recognizing the faces of the cars driven by AI is all Deep Learning. 

Deep Learning can be recognized in photo recognition to finance and health care. In healthcare deep Learning has its contribution in disease prediction, drug discovery, and medical image analysis. Also, self-driving cars use deep learning to understand the environment, make predictions, etc. This helps in safe driving technology.

Deep Learning plays a big role in finance also. It helps in finding any fraud, credit scoring, and algorithmic trading. It can also analyze marketing and financial trends.

Drawbacks

 

With all these advantages and advancements, deep knowledge also has disadvantages or drawbacks. It includes high costs as it needs more resources to train, lack of interpretability as the deep learning models with more layers are complex, and overfitting means poor performance during a new data. More than these data privacy and security concerns, data quality, etc are also some other disadvantages.

Conclusion

In this ever-changing economy, the only constant thing is change. Deep Learning is like a partition in front of Artificial Intelligence. Deep Learning enhances the reason for all those more big surprises and fascination out there to see. Deep Learning is transforming day by day with new kinds of innovations in it. By making the machines have better decision-making capacity and also learn from the vast amount of data, deep learning is shaping everything in miraculous ways.