What is the difference between machine learning algorithm and deep learning?

1. machine learning algorithm: it is a multi-domain interdisciplinary subject, involving probability theory, statistics, approximation theory, convex analysis, algorithm complexity theory and other disciplines.

2. Deep learning: It is a new research direction in the field of machine learning (ML), and it is introduced into machine learning to make it closer to the original goal of artificial intelligence.

Second, the learning process is different

1, machine learning algorithm: the basic structure of learning system. The environment provides some information to the learning part of the system, and the learning part uses this information to modify the knowledge base to improve the efficiency of the system execution part to complete the task. The execution part completes the task according to the knowledge base and feeds back the obtained information to the learning part.

2. Deep learning: By designing and establishing an appropriate number of neuron computing nodes and multi-layer computing levels, choosing an appropriate input layer and output layer, and by learning and optimizing the network, the functional relationship from input to output is established. Although the functional relationship between input and output cannot be found in 100%, it can be as close to reality as possible.

Third, the application is different.

1, machine learning algorithms: data mining, computer vision, natural language processing, biometrics, search engines, medical diagnosis, DNA sequencing, voice and handwriting recognition, strategic games and robot applications.

2. Deep learning: computer vision, speech recognition, natural language processing and other fields.

Baidu Encyclopedia-Machine Learning Algorithm

Baidu encyclopedia-deep learning