List the concepts that should be learned before approaching the given complex concept. Deep Learning

Before approaching the concept of Deep Learning , it is important to have a strong foundation in the following concepts : \n \n 1 . Linear Al gebra : Deep Learning re lies heavily on linear algebra concepts such as matrix operations , linear transformations , and eigen ve ctors . \n 2 . Calcul us : A solid understanding of calculus is necessary to understand the optimization techniques used in Deep Learning , such as gradient descent . \n 3 . Pro b ability and Statistics : Deep Learning models are often used for tasks involving probability and statistics , such as classification and regression . \n 4 . Computer V ision : Deep Learning models are commonly used in computer vision tasks , such as image classification and object detection . \n 5 . Ne ural Network s : A basic understanding of neural networks is necessary to understand how Deep Learning models work . \n 6 . Program ming : Prof ic iency in programming languages such as Python and C ++ is essential for implementing and training Deep Learning models . \n 7 . Data Pre processing : Under standing how to pre process and clean data is cru cial for building effective Deep Learning models . </s>