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This full course video on Neural Network tutorial will help you understand what a neural network is, how it works, and what are the different types of neural networks. You will learn how each neuron processes data, what are activation functions, and how a neuron fires. You will get an idea about backpropagation and gradient descent algorithms. You will have a look at the convolution neural network and how it identifies objects in an image. Finally, you will understand the recurrent neural networks and lSTM in detail.
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Below topics are explained in this Neural Network Full Course:
1. Animated Video
2. What is A Neural Network
3. What is Deep Learning
4. What is Artificial Neural Network
5. How Does Neural Network Works
6. Advantages of Neural Network
7. Applications of Neural Network
8. Future of Neural Network
9. How Does Neural Network Works
10. Types of Artificial Neural Network
11. Use Case-Problem Statement
12. Use Case-Implementation
13. Backpropagation & Gradient Descent
14. Loss Function
15. Gradient Descent
16. Backpropagation
17. Convolutional Neural Network
18. How Image recognition Works
19. Introduction to CNN
20. What is Convolutional Neural Network
21. How CNN recognize Images
22. Layers in Convolutional Neural Network
23. Use Case implementation using CNN
24. What is a Neural Network
25. Popular Neural Network
26. Why Recurrent Neural Network
27. Applications of Recurrent Neural Network
28. how does a RNN works
29. vanishing And Exploding Gradient Problem
30. Long short term Memory
31. use case implementation of LSTM
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#NeuralNetwork #NeuralNetworkFullCourse #NeuralNetworkTutorial #WhatIsNeuralNetwork #DeepLearning #DeepLearningTutorial #DeepLearningCourse #DeepLearningExplained #Simplilearn
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.
You can gain in-depth knowledge of Deep Learning by taking our Deep Learning certification training course. 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
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