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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Why Neural Networks Aren’t Neural Networks
There is a better way to understand how AIs sort data, process images, and make decisions. Source code available here: https://gitlab.com/samsartor/nn_vis
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Neural Network Simply Explained – ML for Beginners
In this video, Mariya from Python Simplified talks about neural networks and some of their basic components. Time stamps: 00:00 – What is a Neural Network 00:55 – How Computers See Images 02:20 – What is a Label 02:44 – Hidden Layers 03:48 – Training 04:10 – Weights 04:42 – Optimization 05:27 – Narrow AI […]
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How Do Neural Networks Grow Smarter?
Neurobiologists and computer scientists are trying to discover how neural networks become a brain. Will nature give us the answer, or is it all up to an artificial intelligence to work it out? Watch this talk from The Royal Institution to find out more.
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Are Quantum Neural Networks Relevant?
Classical neural networks have proven to be extremely powerful models that learn from data. Proposing a quantum variation of these already-so-successful models requires good reason. In this talk, Amira Abbas discusses how to quantify these properties and demonstrate that quantum neural networks can show potential on these fronts, but many open questions remain.
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Do Neural Networks Think Like Our Brain?
Two Minute Papers examines the paper “Multimodal Neurons in Artificial Neural Networks.”
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A Basic Design Pattern for Image Recognition
Design patterns have been in use in the software engineering world for quite some time. A design pattern implies that there is a “best practice” for constructing and coding a model that can be reapplied across a wide range of cases, such as image classification, object detection and tracking, facial recognition, image segmentation, super resolution […]
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