Introduction to AI
Deep Learning is a subset of machine learning that uses neural networks with multiple layers to model and solve complex problems. The term 'deep' refers to the number of layers used in the neural network, with deep networks having multiple layers of nodes between the input and output layers. Deep learning has been used to achieve state-of-the-art results in many fields, including computer vision, natural language processing, and speech recognition.
One common type of deep learning network is the convolutional neural network (CNN). CNNs are often used for image classification tasks, where the network learns to recognize patterns in images. For example, a CNN could be trained to recognize cats in images by analyzing the features of cat images and learning to distinguish them from other images.
Another type of deep learning network is the recurrent neural network (RNN). RNNs are often used for sequence data, such as natural language processing, where the network learns to predict the next word in a sentence based on the previous words.
Deep learning has many applications in everyday life, including facial recognition on social media platforms, speech recognition on virtual assistants, and image recognition in self-driving cars. However, the use of deep learning models also raises concerns about privacy, bias, and ethics, which must be carefully considered when developing and deploying these models.
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