How can Neural Networks learn (almost) anything
They seem magical, but the functioning of neural networks is real and fantastic. A video about neural networks, how they work, and why they’re useful.
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Running Neural Networks on Meshes of Light
Photonics are not just for quantum computers apparently. Could we be on the precipice of a new hardware paradigm?
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How Deep Neural Networks Work
This is part of the End-to-End Machine Learning School Course 193, How Neural Networks Work at https://e2eml.school/193
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Introduction to Long Short-Term Memory Networks (LSTM)
-
Frank
- August 8, 2022
- 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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Building a neural network FROM SCRATCH (no Tensorflow/Pytorch, just numpy & math)
Watch the video and check out the Kaggle notebook with all the code.
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Sigmoid Activation Function – Deep Learning Dictionary
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Frank
- July 11, 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 is the sigmoid activation function used in artificial neural networks?
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Developer Tech Minutes: Swin Transformer
Microsoft researchers developed Swin Transformer, a new model architecture that has significantly outperformed previous dominant convolutional neural networks on broad vision problems. In version 2 of Swin Transformer, they then joined this new architecture with a new learning approach, known as SimMIM, or “A Simple Framework for Masked Image Modeling.” In this Tech Minutes episode, […]
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Transfer learning and Transformer models (ML Tech Talks)
-
Frank
- June 20, 2022
- Developer
- Developers
- GDS: Yes
- Google Developers
- how to use machine learning
- how to use ml
- Iulia Turc
- machine learning tech talks
- machine learning tutorial
- ml tutorial
- pr_pr: TensorFlow
- purpose: Educate
- series: ML Tech Talks
- TensorFlow
- tensorflow developer
- tensorflow developers
- the transformer
- Transfer Learning
- transformer models
- type: DevByte (deck cleanup 0-10min)
- what is machine learning
- what is ML
In this session of Machine Learning Tech Talks, Software Engineer from Google Research, Iulia Turc, will walk us through the recent history of natural language processing, including the current state of the art architecture, the Transformer.
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Illustrated Guide to Transformers Neural Network: A step by step explanation
Transformers are the rage nowadays, but how do they work? This video demystifies the novel neural network architecture with step by step explanation and illustrations on how transformers work. CORRECTIONS: The sine and cosine functions are actually applied to the embedding dimensions and time steps!
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Neural Networks Explained in 5 minutes
Neural networks reflect the behavior of the human brain, allowing computer programs to recognize patterns and solve common problems in the fields of AI, machine learning, and deep learning. Master Inventor, Martin Keen, makes some important points about neural networks and does it all in 5 minutes.
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