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Fundamentals of Neural Networks - VGG16
This video explains VGG16 which is a convolutional neural network model proposed by K. Simonyan and A. Zisserman from the University of Oxford in the paper "Very Deep Convolutional Networks for Large-Scale Image Recognition". This clip...
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Fundamentals of Neural Networks - Convolution in 2D and 3D
This video explains Convolution in 2D and 3D. This clip is from the chapter "Convolutional Neural Networks" of the series "Fundamentals in Neural Networks".This section explains convolutional neural networks where you will start with...
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Fundamentals of Neural Networks - Stride
For a convolutional or pooling operation, the stride denotes the number of pixels by which the window moves after each operation. This clip is from the chapter "Convolutional Neural Networks" of the series "Fundamentals in Neural...
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Fundamentals of Neural Networks - Padding
This video explains padding in convolutional neural networks. This clip is from the chapter "Convolutional Neural Networks" of the series "Fundamentals in Neural Networks".This section explains convolutional neural networks where you...
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Fundamentals of Neural Networks - Convolutional Operation
The Convolution layer (CONV) uses filters that perform convolution operations as it is scanning the input with respect to its dimensions. Its hyperparameters include the filter size and stride. The resulting output is called a feature...
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Fundamentals of Neural Networks - Tensor and Matrix
This video explains what we mean by Tensor and Matrix. This clip is from the chapter "Convolutional Neural Networks" of the series "Fundamentals in Neural Networks".This section explains convolutional neural networks where you will start...
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Fundamentals of Neural Networks - Image Data
This video explains image data in CNN (Convolutional Neural Network). This clip is from the chapter "Convolutional Neural Networks" of the series "Fundamentals in Neural Networks".This section explains convolutional neural networks where...
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Fundamentals of Neural Networks - Lab 5 - Building Deeper and Wider Model
This video demonstrates how to build a deeper and wider neural network model. This clip is from the chapter "Artificial Neural Networks" of the series "Fundamentals in Neural Networks".This section explains artificial neural networks...
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Fundamentals of Neural Networks - Gradient Descent
This video explains the optimization problem using the gradient descent algorithm. This clip is from the chapter "Artificial Neural Networks" of the series "Fundamentals in Neural Networks".This section explains artificial neural...
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Fundamentals of Neural Networks - Cross-Entropy Loss Function
This video explains the cross-entropy function, which is designed under the assumption that the variable you are trying to predict is binary. This clip is from the chapter "Artificial Neural Networks" of the series "Fundamentals in...
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Fundamentals of Neural Networks - Activation Function
This video explains the role of the activation function, which is an interesting phenomenon in the design of neural networks. This clip is from the chapter "Artificial Neural Networks" of the series "Fundamentals in Neural Networks".This...
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Fundamentals of Neural Networks - Backward Propagation
This video explains backward propagation, which is defined by the optimization problem called the gradient descent algorithm. This clip is from the chapter "Artificial Neural Networks" of the series "Fundamentals in Neural Networks".This...
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Fundamentals of Neural Networks - Forward Propagation
This video explains forward propagation and will dive deeper into the architecture of neural networks. This clip is from the chapter "Artificial Neural Networks" of the series "Fundamentals in Neural Networks".This section explains...
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Fundamentals of Neural Networks - Purpose of Neural Networks
This video explains the purpose of neural networks. This clip is from the chapter "Artificial Neural Networks" of the series "Fundamentals in Neural Networks".This section explains artificial neural networks where you will learn every...
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Fundamentals of Neural Networks - Logistic Regression
This video explains logistic regression and specifically if the target here is discrete or binary. This clip is from the chapter "Artificial Neural Networks" of the series "Fundamentals in Neural Networks".This section explains...
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Fundamentals of Neural Networks - Linear Regression
This video explains statistical machine learning, where you will start with the linear regression model. This clip is from the chapter "Artificial Neural Networks" of the series "Fundamentals in Neural Networks".This section explains...
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Fundamentals of Neural Networks - Course Outline
This video explains the course outline and what the course has to offer. This clip is from the chapter "Welcome" of the series "Fundamentals in Neural Networks".This section introduces you to the course and the course outline.
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Fundamentals of Neural Networks - Welcome Message
This video explains the need for taking up the course and introduces you to the author. This clip is from the chapter "Welcome" of the series "Fundamentals in Neural Networks".This section introduces you to the course and the course...
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Deep Learning - Convolutional Neural Networks with TensorFlow - Outline
In this video, we will understand the course learning approach and what is required to start with this course. Then we will also understand what is covered in this course. This clip is from the chapter "Welcome" of the series "Deep...
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Deep Learning - Convolutional Neural Networks with TensorFlow - Introduction
In this video, we will introduce the author and understand the course learning objective. This clip is from the chapter "Welcome" of the series "Deep Learning - Convolutional Neural Networks with TensorFlow".Welcome to the course! In...
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Deep Learning - Convolutional Neural Networks with TensorFlow - Transfer Learning Code (Part 2)
In this video, we will dive into action and look at codes for transfer learning without data augmentation. This clip is from the chapter "Transfer Learning for Computer Vision" of the series "Deep Learning - Convolutional Neural Networks...
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Deep Learning - Convolutional Neural Networks with TensorFlow - Transfer Learning Code (Part 1)
In this video, we will dive into action and look at codes for transfer learning with data augmentation. This clip is from the chapter "Transfer Learning for Computer Vision" of the series "Deep Learning - Convolutional Neural Networks...
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Deep Learning - Convolutional Neural Networks with TensorFlow - Large Datasets and Data Generators
In this video, you will learn how to work with large image datasets in TensorFlow and Keras with data generators. This clip is from the chapter "Transfer Learning for Computer Vision" of the series "Deep Learning - Convolutional Neural...
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Deep Learning - Convolutional Neural Networks with TensorFlow - Transfer Learning Theory
In this video, we will get introduced to the concept of transfer learning. This clip is from the chapter "Transfer Learning for Computer Vision" of the series "Deep Learning - Convolutional Neural Networks with TensorFlow".In this...