Neural Network Layers – Deep Learning Dictionary
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Frank
- May 16, 2022
- 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
What are the layers that make up an artificial neural network?
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Sparse Expert Models (Switch Transformers, GLAM, and more… w/ the Authors)
This video is an interview with Barret Zoph and William Fedus of Google Brain about Sparse Expert Models. Sparse Expert models have been hugely successful at distributing parts of models, mostly Transformers, across large array of machines and use a routing function to effectively route signals between them. This means that even though these models […]
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Why Neural Networks can learn almost anything
A video that explains neural networks, how they work, and why they’re useful.
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Recurrent Neural Networks Tutorial
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Frank
- March 14, 2022
- Deep Learning
- deep learning edureka
- deep learning tutorial
- deep learning using tensorflow
- edureka
- lstm neural network
- lstm python tutorial
- recurrent neural network based language model
- recurrent neural network explained
- recurrent neural network lstm
- recurrent neural network tutorial
- recurrent neural network tutorial tensorflow
- recurrent neural networks
- rnn lstm
- rnn tensorflow
- rnn tensorflow tutorial
- rnn tutorial
- tensorflow tutorial
This Edureka Recurrent Neural Networks tutorial video will help you in understanding why we need Recurrent Neural Networks (RNN) and what exactly it is. It also explains few issues with training a Recurrent Neural Network and how to overcome those challenges using LSTMs. The last section includes a use-case of LSTM to predict the next […]
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Artificial Neural Networks Tutorial
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Frank
- January 28, 2022
- artificial neural network
- artificial neural network applications
- artificial neural network lecture
- artificial neural network python
- artificial neural network tutorial
- backpropagation in neural networks
- backpropagation tutorial
- deep learning edureka
- deep learning with neural networks
- edureka
- Neural Network
- neural network example
- neural network python
- neural network tutorial
- neural network tutorial python
- tensorflow edureka
This Edureka “Neural Network Tutorial” video (Blog: https://goo.gl/4zxMfU) will help you to understand the basics of Neural Networks and how to use it for deep learning. It explains Single layer and Multi layer Perceptron in detail. Time stamps: 00:00 Introduction 00:42 Agenda 01:02 Why Neural Networks 02:24 Motivation behind Neural Networks 04:46 What are Neural […]
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DIABLo: a Deep Individual
Here’s an interesting video from Microsoft Research In this project, we have developed and studied a deep neural network-based individual-agnostic general-purpose binaural localizer (BL) for sound sources located at arbitrary directions on the $4\pi$ sphere. Unlike binaural localization models trained with an HRIR catalog associated with a specific head and ear shape, an individual-agnostic model […]
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Challenges of Training Large-Scale Neural Networks
Here’s an interesting look at the unique challenges that present themselves when training large neural networks.
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Neural Networks from the Ground Up
I recently delivered this talk at the Northern Virginia (NoVA) Code Camp. Neural networks are an essential element of many advanced artificial intelligence (AI) solutions. However, few people understand the core mathematical or structural underpinnings of this concept. In this session, learn the basic structure of neural networks and how to build out a simple […]
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Making Neural Networks Portable with ONNX
The world of machine learning frameworks is complex. What if we can use the lightest framework for inferencing on edge devices? That’s the idea behind ONNX format. Attend this session and find out how to train models using the framework of your choice, save or convert models into ONNX, and deploy to cloud and edge […]
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Introduction to Long Short-Term Memory Networks (LSTM)
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Frank
- October 29, 2021
- Deep Learning
- deep learning edureka
- deep learning tutorial
- edureka
- long term short
- lstm explained
- lstm neural network
- lstm python tutorial
- recurrent neural network based language model
- recurrent neural network explained
- recurrent neural network lstm
- recurrent neural network tutorial
- recurrent neural network tutorial tensorflow
- recurrent neural networks
- rnn lstm
- rnn tensorflow
- rnn tensorflow tutorial
- rnn tutorial
- tensorflow tutorial
This Edureka LSTM Explained video will help you in understanding why we need Recurrent Neural Networks (RNN) and what exactly it is. It also explains few issues with training a Recurrent Neural Network and how to overcome those challenges using LSTMs.
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