Deep Learning and Machine Learning are subsets of Artificial Intelligence. These intelligent processes consist of learning, reasoning, and self-correction.
Artificial Intelligence is a vast advancement in the technology sector. It utilizes human intelligence and is implemented by machines.
The fig. below depicts a clear representation of the matter:
Before knowing the differences between deep learning and machine learning, it's important to understand both the terms precisely.
Deep learning is a part of artificial intelligence that functions by imitating the workings of the human brain in data processing and creating patterns that can be effectively used in decision making.
Deep learning originated from artificial intelligence (AI) that features networks capable of learning unsupervised from data that is unstructured or unlabeled.
Machine learning is a faction of artificial intelligence (AI) that offers systems the potential to understand and modify from experience without being required to explicitly programmed.
Machine learning emphasizes on the development of computer programs that can identify patterns, learn from data and can operate with minimum human help.
Major Differences between Deep Learning and Machine Learning:
The significant and critical difference between deep learning and machine learning is classified in the way data is presented to the system.
Listing out a few more differences to make you clear about the differences between deep learning and machine learning:
Conclusion: The most straightforward way for understanding the difference between machine learning and deep learning is to understand the fact that deep learning is machine learning. More specifically, deep learning is considered as an evolution of machine learning. It utilizes a programmable neural network that provides an opportunity for the machines to make accurate decisions without human intervention.