Common deep learning applications include . . . . . . . .

Image classification, Real-time visual tracking
Autonomous car driving, Logistic optimization
Bioinformatics, Speech recognition
All above

The correct answer is D. All above.

Deep learning is a type of machine learning that uses artificial neural networks to solve complex problems. It has been used in a wide variety of applications, including image classification, real-time visual tracking, autonomous car driving, logistic optimization, bioinformatics, and speech recognition.

Image classification is the task of assigning a label to an image, such as “cat” or “dog.” Deep learning has been used to achieve state-of-the-art results on image classification tasks.

Real-time visual tracking is the task of tracking the movement of an object in a video stream. Deep learning has been used to achieve real-time performance on this task.

Autonomous car driving is the task of driving a car without human input. Deep learning has been used to achieve state-of-the-art results on this task.

Logistic optimization is the task of finding the best way to allocate resources to meet a set of goals. Deep learning has been used to achieve state-of-the-art results on this task.

Bioinformatics is the field of science that deals with the collection, storage, analysis, and dissemination of biological data. Deep learning has been used to achieve state-of-the-art results on a variety of bioinformatics tasks, such as protein folding and gene expression analysis.

Speech recognition is the task of converting spoken language into text. Deep learning has been used to achieve state-of-the-art results on this task.

In addition to the applications listed above, deep learning has also been used in a variety of other areas, such as natural language processing, fraud detection, and medical diagnosis.

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