Machine learning (ML), artificial intelligence (AI), and deep learning (DL) are related but distinct fields.
Artificial intelligence is a broad field that encompasses a wide range of technologies and applications, including machine learning. AI involves the development of intelligent machines that can perform tasks that typically require human intelligence. AI can be divided into two categories: narrow or weak AI and general or strong AI.
Machine learning is a subfield of AI that focuses on teaching machines to learn patterns and make predictions based on data. ML algorithms allow machines to automatically improve their performance with experience, without being explicitly programmed. Machine learning can be supervised, unsupervised, or semi-supervised, depending on the type of input data and the type of output that the algorithm produces.
Deep learning is a subfield of machine learning that involves the use of neural networks with multiple layers to learn complex patterns in data. Deep learning algorithms are particularly effective at image recognition, natural language processing, and speech recognition. Deep learning models can be trained on large datasets and can automatically learn hierarchical representations of features in the data.
In summary, machine learning is a subset of artificial intelligence that enables machines to learn from data and improve their performance with experience. Deep learning is a subfield of machine learning that involves the use of neural networks with multiple layers to learn complex patterns in data. Artificial intelligence is a broader field that encompasses a wide range of technologies and applications, including machine learning and deep learning.