Intuitive Intro To Generative Adversarial Networks – GAN Course Preview
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Frank
- July 26, 2021
- activation function
- AI
- artificial intelligence
- artificial neural network
- Autoencoders
- batch normalization
- CNN
- Convolutional Neural Network
- CUDA
- cuDNN
- data augmentation
- Deep Learning
- Education
- fine-tune
- GANS
- generative adversarial networks
- GPU
- image classification
- Keras
- Learning
- Machine Learning
- neural net
- Neural Network
- Nvidia
- Python
- PyTorch
- relu
- SGD
- Supervised Learning
- TensorFlow
- tensorflow.js
- train
- Training
- Transfer Learning
- Tutorial
- Unsupervised Learning
deeplizard has a brand new premium course, an Introduction to Generative Adversarial Networks (GANs). Below is the full first lesson of the course available as a preview to the course at large.
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Intro to Generative Adversarial Networks (GANs) – New Course Release
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Frank
- July 19, 2021
- activation function
- AI
- artificial intelligence
- artificial neural network
- Autoencoders
- batch normalization
- CNN
- Convolutional Neural Network
- CUDA
- cuDNN
- data augmentation
- Deep Learning
- Education
- fine-tune
- GANS
- generative adversarial networks
- GPU
- image classification
- Keras
- Learning
- Machine Learning
- neural net
- Neural Network
- Nvidia
- Python
- PyTorch
- relu
- SGD
- Supervised Learning
- TensorFlow
- tensorflow.js
- train
- Training
- Transfer Learning
- Tutorial
- Unsupervised Learning
deeplizard announces their brand new premium deeplizard course, an Introduction to Generative Adversarial Networks (GANs)
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Convolutions in Deep Learning – Interactive Demo App
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Frank
- June 6, 2021
- activation function
- AI
- artificial intelligence
- artificial neural network
- Autoencoders
- batch normalization
- Clustering
- CNN
- Convolutional Neural Network
- CUDA
- cuDNN
- data augmentation
- Deep Learning
- Education
- fine-tune
- GPU
- image classification
- Keras
- Learning
- Machine Learning
- neural net
- Neural Network
- Nvidia
- Python
- PyTorch
- relu
- Sequential model
- SGD
- Supervised Learning
- TensorFlow
- tensorflow.js
- TFJS
- train
- Training
- Transfer Learning
- Tutorial
- Unsupervised Learning
deeplizard explains the importance of convolutions in deep learning. In deep learning, convolution operations are the key components used in convolutional neural networks. A convolution operation maps an input to an output using a filter and a sliding window. Use the interactive demonstration below to gain a better understanding of this process.
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Data Augmentation with TensorFlow’s Keras API
-
Frank
- October 14, 2020
- activation function
- AI
- artificial intelligence
- artificial neural network
- Autoencoders
- batch normalization
- Clustering
- CNN
- Convolutional Neural Network
- CUDA
- cuDNN
- data augmentation
- Deep Learning
- Education
- fine-tune
- GPU
- image classification
- Keras
- Learning
- Machine Learning
- neural net
- Neural Network
- Nvidia
- Python
- PyTorch
- relu
- Sequential model
- SGD
- Supervised Learning
- TensorFlow
- tensorflow.js
- TFJS
- train
- Training
- Transfer Learning
- Tutorial
- Unsupervised Learning
deeplizard demonstrates how to use data augmentation on images using TensorFlow’s Keras API. VIDEO SECTIONS 00:00 Welcome to DEEPLIZARD – Go to deeplizard.com for learning resources 00:17 Introduction to Data Augmentation 01:32 Image Augmentation with Keras 08:16 Collective Intelligence and the DEEPLIZARD HIVEMIND
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Fine-Tuning MobileNet on Custom Dataset with TensorFlow’s Keras API
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Frank
- September 28, 2020
- activation function
- AI
- artificial intelligence
- artificial neural network
- Autoencoders
- batch normalization
- Clustering
- CNN
- Convolutional Neural Network
- CUDA
- cuDNN
- data augmentation
- Deep Learning
- Education
- fine-tune
- GPU
- image classification
- Keras
- Learning
- Machine Learning
- neural net
- Neural Network
- Nvidia
- Python
- PyTorch
- relu
- Sequential model
- SGD
- Supervised Learning
- TensorFlow
- tensorflow.js
- train
- Training
- Transfer Learning
- Tutorial
- Unsupervised Learning
In this episode, Mandy from deeplizard will be building on what we’ve learned about MobileNet combined with the techniques we’ve used for fine-tuning to fine-tune MobileNet for a custom image data set using TensorFlow’s Keras API.
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Process Images for Fine-Tuned MobileNet with TensorFlow’s Keras API
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Frank
- September 14, 2020
- activation function
- AI
- artificial intelligence
- artificial neural network
- Autoencoders
- batch normalization
- Clustering
- CNN
- Convolutional Neural Network
- CUDA
- cuDNN
- data augmentation
- Deep Learning
- Education
- fine-tune
- GPU
- image classification
- Keras
- Learning
- Machine Learning
- neural net
- Neural Network
- Nvidia
- Python
- PyTorch
- relu
- Sequential model
- SGD
- Supervised Learning
- TensorFlow
- tensorflow.js
- TFJS
- train
- Training
- Transfer Learning
- Tutorial
- Unsupervised Learning
In this deeplizard episode, learn how to prepare and process our own custom data set of sign language digits, which will be used to train our fine-tuned MobileNet model in a future episode. VIDEO SECTIONS 00:00 Welcome to DEEPLIZARD – Go to deeplizard.com for learning resources 00:40 Obtain the Data 01:30 Organize the Data 09:42 […]
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MobileNet Image Classification with TensorFlow’s Keras API
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Frank
- September 8, 2020
- activation function
- AI
- artificial intelligence
- artificial neural network
- Autoencoders
- batch normalization
- Clustering
- CNN
- Convolutional Neural Network
- CUDA
- cuDNN
- data augmentation
- Deep Learning
- Education
- fine-tune
- GPU
- image classification
- Keras
- Learning
- Machine Learning
- neural net
- Neural Network
- Nvidia
- Python
- PyTorch
- relu
- Sequential model
- SGD
- Supervised Learning
- TensorFlow
- tensorflow.js
- TFJS
- train
- Training
- Transfer Learning
- Tutorial
- Unsupervised Learning
deeplizard introduces MobileNets, a class of light weight deep convolutional neural networks that are vastly smaller in size and faster in performance than many other popular models. VIDEO SECTIONS 00:00 Welcome to DEEPLIZARD – Go to deeplizard.com for learning resources 00:17 Intro to MobileNets 02:56 Accessing MobileNet with Keras 07:25 Getting Predictions from MobileNet 13:32 […]
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Visualizing Deep Learning
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Frank
- September 2, 2020
- 3b1b
- A Visual Introduction
- Alfredo canziani
- animation
- ann
- artificial intelligence
- artificial neural network
- Calculus
- CNN
- Deep Learning
- derivative
- dl
- Machine Learning
- manim
- Math
- Neural Network
- Neural Networks
- neural networks visualized
- nn
- NYU
- structure
- structure of neural networks
- The Neural Network
- v cubing x
- vcubing x
- vcubingx
- Visualization
- visualizing deep learning
- visualizing neural networks
- vivek verma
- Yann LeCun
vcubingx provides a visual introduction to the structure of an artificial neural network. The Neural Network, A Visual Introduction | Visualizing Deep Learning, Chapter 1 0:00 Intro 1:55 One input Perceptron 3:30 Two input Perceptron 4:40 Three input Perceptron 5:17 Activation Functions 6:58 Neural Network 9:45 Visualizing 2-2-2 Network 10:59 Visualizing 2-3-2 Network 12:33 Classification […]
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Predict with a Fine-Tuned Neural Network with TensorFlow’s Keras API
-
Frank
- August 26, 2020
- activation function
- AI
- artificial intelligence
- artificial neural network
- Autoencoders
- batch normalization
- Clustering
- CNN
- Convolutional Neural Network
- CUDA
- cuDNN
- data augmentation
- Deep Learning
- Education
- fine-tune
- GPU
- image classification
- Keras
- Learning
- Machine Learning
- neural net
- Neural Network
- Nvidia
- Python
- PyTorch
- relu
- Sequential model
- SGD
- Supervised Learning
- TensorFlow
- tensorflow.js
- TFJS
- train
- Training
- Transfer Learning
- Tutorial
- Unsupervised Learning
In this video, Mandy from deeplizard demonstrates how to use the fine-tuned VGG16 Keras model that we trained in the last episode to predict on images of cats and dogs in our test set. Index: 00:00 Welcome to DEEPLIZARD – Go to deeplizard.com for learning resources 00:17 Predict with a Fine-tuned Model 05:40 Plot Predictions […]
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Build a Fine-Tuned Neural Network with TensorFlow’s Keras API
-
Frank
- August 11, 2020
- activation function
- AI
- artificial intelligence
- artificial neural network
- Autoencoders
- batch normalization
- Clustering
- CNN
- Convolutional Neural Network
- CUDA
- cuDNN
- data augmentation
- Deep Learning
- Education
- fine-tune
- GPU
- image classification
- Keras
- Learning
- Machine Learning
- neural net
- Neural Network
- Nvidia
- Python
- PyTorch
- relu
- Sequential model
- SGD
- Supervised Learning
- TensorFlow
- tensorflow.js
- TFJS
- train
- Training
- Transfer Learning
- Tutorial
- Unsupervised Learning
In this video, Mandy from deeplizard demonstrate how to fine-tune a pre-trained model called VGG16 to classify images as cats and dogs.
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