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This video on backpropagation and gradient descent will cover the basics of how backpropagation and gradient descent plays a role in training neural networks - using an example on how to recognize the handwritten digits using a neural network. After predicting the results, you will see how to train the network using backpropagation to obtain the results with high accuracy. Backpropagation is the process of updating the parameters of a network to reduce the error in prediction. You will also understand how to calculate the loss function to measure the error in the model. Finally, you will see with the help of a graph, how to find the minimum of a function using gradient descent.

Free Deep Learning Course: https://www.simplilearn.com/introduction-to-deep-learning-free-course-skillup?utm_campaign=BackPropagationandGradientDescent&utm_medium=Description&utm_source=youtube

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To access the slides, click here: https://www.slideshare.net/Simplilearn/how-to-become-a-digital-marketer-how-to-start-career-in-digital-marketing-in-2019-simplilearn/Simplilearn/how-to-become-a-digital-marketer-how-to-start-career-in-digital-marketing-in-2019-simplilearn

To access the slides, click here: https://www.slideshare.net/Simplilearn/backpropagation-and-gradient-descent-in-neural-networks-neural-network-tutorial-simplilearn/Simplilearn/backpropagation-and-gradient-descent-in-neural-networks-neural-network-tutorial-simplilearn

Watch more videos on Deep Learning: https://www.youtube.com/watch?v=FbxTVRfQFuI&list=PLEiEAq2VkUUIYQ-mMRAGilfOKyWKpHSip

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Simplilearn’s Deep Learning course will transform you into an expert in deep learning techniques using TensorFlow, the open-source software library designed to conduct machine learning & deep neural network research. With our deep learning course, you'll master deep learning and TensorFlow concepts, learn to implement algorithms, build artificial neural networks and traverse layers of data abstraction to understand the power of data and prepare you for your new role as deep learning scientist.

With Simplilearn’s Deep Learning course, you will prepare for a career as a Deep Learning engineer as you master concepts and techniques including supervised and unsupervised learning, mathematical and heuristic aspects, and hands-on modeling to develop algorithms. Those who complete the course will be able to:

1. Understand the concepts of TensorFlow, its main functions, operations and the execution pipeline
2. Implement deep learning algorithms, understand neural networks and traverse the layers of data abstraction which will empower you to understand data like never before
3. Master and comprehend advanced topics such as convolutional neural networks, recurrent neural networks, training deep networks and high-level interfaces
4. Build deep learning models in TensorFlow and interpret the results
5. Understand the language and fundamental concepts of artificial neural networks
6. Troubleshoot and improve deep learning models
7. Build your own deep learning project
8. Differentiate between machine learning, deep learning and artificial intelligence

We recommend this deep learning online course particularly for the following professionals:
1. Software engineers
2. Data scientists
3. Data analysts
4. Statisticians with an interest in deep learning

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