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You're reading from  Deep Learning for Beginners

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Published inSep 2020
Reading LevelBeginner
PublisherPackt
ISBN-139781838640859
Edition1st Edition
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Dr. Pablo Rivas
Dr. Pablo Rivas
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Dr. Pablo Rivas

Dr. Pablo Rivas is an assistant professor of computer science at Baylor University in Texas. He worked in industry for a decade as a software engineer before becoming an academic. He is a senior member of the IEEE, ACM, and SIAM. He was formerly at NASA Goddard Space Flight Center performing research. He is an ally of women in technology, a deep learning evangelist, machine learning ethicist, and a proponent of the democratization of machine learning and artificial intelligence in general. He teaches machine learning and deep learning. Dr. Rivas is a published author and all his papers are related to machine learning, computer vision, and machine learning ethics. Dr. Rivas prefers Vim to Emacs and spaces to tabs.
Read more about Dr. Pablo Rivas

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Introducing deep learning

While a more detailed discussion of learning algorithms will be addressed in Chapter 4, Learning from Data, in this section, we will deal with the fundamental concept of a neural network and the developments that led to deep learning.

The model of a neuron

The human brain has input connections from other neurons (synapses) that receive stimuli in the form of electric charges, and then has a nucleus that depends on how the input stimulates the neuron that can trigger the neuron's activation. At the end of the neuron, the output signal is propagated to other neurons through dendrites, thus forming a network of neurons.

The analogy of the human neuron is depicted in Figure 1.3, where the input is represented with the vector x, the activation of the neuron is given by some function z(.), and the output is y. The parameters of the neuron are w and b:

Figure 1.3 - The basic model of a neuron

The trainable parameters of a neuron are w and b, and they are unknown...

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Author (1)

author image
Dr. Pablo Rivas

Dr. Pablo Rivas is an assistant professor of computer science at Baylor University in Texas. He worked in industry for a decade as a software engineer before becoming an academic. He is a senior member of the IEEE, ACM, and SIAM. He was formerly at NASA Goddard Space Flight Center performing research. He is an ally of women in technology, a deep learning evangelist, machine learning ethicist, and a proponent of the democratization of machine learning and artificial intelligence in general. He teaches machine learning and deep learning. Dr. Rivas is a published author and all his papers are related to machine learning, computer vision, and machine learning ethics. Dr. Rivas prefers Vim to Emacs and spaces to tabs.
Read more about Dr. Pablo Rivas