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Difference Between Machine Learning Vs Deep Learning?


What Is The Difference Between Machine Learning Vs Deep Learning?

Machine learning is a subset, an application of Artificial Intelligence (AI) that offers the ability to the system to learn and improve from experience without being programmed to that level .Deep Learning is a subset of Machine Learning where the artificial neural network, the recurrent neural network comes in relation. The algorithms are created exactly just like machine learning but it consists of many more levels of algorithms.

Machine Learning uses data to train and find accurate results. Machine learning focuses on the development of a computer program that accesses the data and uses it to learn from them. These networks of the algorithm are together called as the artificial neural network. In much simpler terms, it replicates just like the human brain as all the neural networks are connected in the brain, exactly is the concept of deep learning. It solves all the complex problems with the help of algorithms and its process.

We learned that deep learning is a subset of machine learning, and both types of learning are subfields of artificial intelligence. Many say that deep learning is machine learning. While the two are closely related, they have their differences. Let’s discuss!

Human interference: While machine learning models become better at their specified tasks, they still require our guidance. On the other hand, deep learning algorithms use their neural networks for decision-making and analysis.

Complexity: While both machine learning and deep learning are complex systems, machine learning algorithms have simpler structures, like decision trees or linear regression. Since deep learning is modeled after the human brain, the structure of the ANN is much more complex and interconnected.

Algorithmic differences: Machine learning algorithms are detected by data scientists and analysts, while deep learning algorithms are mainly self-depicted. Data representation: Machine learning algorithms typically require structured data, whereas deep learning algorithms rely on layers of artificial neural networks. Scalability: Machine learning is not as well-suited for solving complex problems with large datasets, but deep learning is.