Learning is a continuous process in the life of a human being, and no amount of learning is enough to solve all problems. Learning something new is very common and not at all surprising in the case of human beings but it is certainly a surprising thing if it happens in the case of a machine. Technology can conquer this. Thanks to technology. Learning is mandatory for everyone and business enterprises are not an exception to it. The origin of any discovery or invention basically lies in its necessity. The emergence of AI has taken the world by storm and today everyone is looking at AI.
Artificial Intelligence, Machine Learning, Deep Learning and Neural Networks are difficult terms to a common man. Only the people with technical knowledge can understand the true difference. In simple terms, AI is a big block to which ML, DL and Neural Networks are branches. Machine Learning is the ability of a machine to perform better based on previous results.
Data is the most crucial component in any of the above technologies. The quality of the data depends on its diversity. If the data is diverse, results are better. Data collection is very important in the entire process though it is tedious and time taking. Manual data collection is error prone and hence it is considered inferior to automatic data collection. Every entity has some specific features. The machine actually looks into these features in the analysis phase. A problem can be solved in many ways, but using the right algorithm gives better results.
Deep Learning is an improvised part of machine learning. In Machine Learning, an input is given at the starting point. Later, the features of the input are analyzed in the feature extraction process. Subsequently, the features are classified according to their common nature. This entire process creates huge data and the machine compares it with the data in which it is embedded. If a bus is given as the input, the machine learns from the algorithms and understands whether the input has the features similar to that of a bus. If they match, the output will be given as bus and if they don’t, the output will be given as no bus. In the case of deep learning, the feature extraction will be done by the machine itself unlike in ML, where it is done by humans. The feature extraction and classification will be done at a single phase by the machine itself and the output is given as bus or no bus. Machine Learning and Deep Learning are the modern-day technological revolutions which can unlock the potential of those enterprises with the passion for development and agility to move with the storm.
Spar Information Systems has the right blend of human potential and technological capabilities to meet the demands of our clients. Our teams bring expertise coupled with deep range of perspectives. We are willing to be a part of your transformation.