Deep learning is a subfield of machine learning technique that teaches computers to perform classification tasks that are directly from images, text or sound. Deep learning models are trained using neural network architectures and labeled data. This new technology is the reason behind the success of driverless cars, which enables them to recognize a stop sign or pedestrian. Apart from this, in many other technologies, deep learning is getting good attention and responses which were not seen before.
If we consider uses of deep learning from work point of view, its application is used from driverless cars to medical applications.
In neuroscience, deep learning is used to identify objects from satellites.
In medical science, cancer researches use deep learning to detect cancer cells.
Other than this, deep learning is used in automated speech translation and hearing.
In deep learning, the important features are automatically extracted from the image and it also helps to perform end-to-end learning. As deep learning is a growing technology, it has a bright future scope and the main reason behind that is it doesn’t require any kind of feature engineering i.e. it extracts the features from data itself and abolishing feature engineering.
We craft deep learning algorithms for a wide array of businesses, that allows us to address various problems that are beyond human capabilities.