A Gentle Introduction to language modeling: building makemore
Andrej Karpathy implements a bigram character-level language model, which we will further complexify in followup videos into a modern Transformer language model, like GPT. In this video, the focus is on (1) introducing torch.Tensor and its subtleties and use in efficiently evaluating neural networks and (2) the overall framework of language modeling that includes model […]
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AI Learns What Pizza Is
Green Code explores Pytorch and machine learning by teaching an AI what Pizza Is. I used CNNs, neural nets, and even some complex networks (like VGG16) to help the AI recognize pizzas.
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Activation Functions – Deep Learning Dictionary
-
Frank
- December 28, 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 activation functions within artificial neural networks? Mandy from deeplizard explains.
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How to Retrain SSD Object Detection Model with Pytorch PART – 1
Interesting tutorial on transfer learning. Transfer Learning with Pytorch Transfer learning is a technique for re-training a DNN model on a new dataset, which takes less time than training a network from scratch. With transfer learning, the weights of a pre-trained model are fine-tuned to classify a customized dataset. In these examples, we’ll be using […]
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Learn PyTorch for deep learning in a day. Literally.
All code on GitHub – https://dbourke.link/pt-github
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Intro to Natural Language Processing (NLP)
-
Frank
- August 22, 2022
- AI
- artificial intelligence
- artificial neural network
- Autoencoders
- Clustering
- Convolutional Neural Network
- CUDA
- cuDNN
- data augmentation
- Deep Learning
- fine-tune
- GPU
- image classification
- Keras
- Learning
- Machine Learning
- Natural Language Processing
- neural net
- Neural Network
- Nvidia
- Python
- PyTorch
- relu
- Sentiment Analysis
- Sequential model
- Supervised Learning
- TensorFlow
- tensorflow.js
- Text Classification
- TFJS
- train
- Training
- Transfer Learning
- Tutorial
- Unsupervised Learning
This course provides an introduction to the field of Natural Language Processing (NLP) with a focus on sentiment analysis and text classification using artificial neural networks. In this lesson, we’ll get introduced to the field of Natural Language Processing, otherwise known simply as NLP.
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Sigmoid Activation Function – Deep Learning Dictionary
-
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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Open Data Hub – the origin story (part 2)
-
Frank
- July 6, 2022
- AI
- AI on Kubernetes
- Ai on OpenShift
- AI/ML
- artificial intelligence
- Data Science
- DevOps
- Git
- Jupyter
- JupyterHub
- JupyterLab
- Machine Learning
- ML
- ML on Kubernetes
- ML on OpenShift
- MLOps
- ODH
- Open Data Hub
- OpenShift
- OpenShift Data Science
- Python
- PyTorch
- Red Hat
- S2i
- Source-to-image
- Spark
- TensorFlow
In part 2 of the Open Data Hub origin story, fellow Red Hatters Steven Huels and Sherard Griffin describe some of the technical challenges and growth of the Open Data Hub AI meta-project, evolving Elastic Search to multiple data discovery technologies. The evolution to a commercial service offering, Red Hat OpenShift Data Science is also […]
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Open Data Hub – the origin story (part 1)
-
Frank
- July 6, 2022
- AI
- AI on Kubernetes
- Ai on OpenShift
- AI/ML
- artificial intelligence
- Data Science
- DevOps
- Git
- Jupyter
- JupyterHub
- JupyterLab
- Machine Learning
- ML
- ML on Kubernetes
- ML on OpenShift
- MLOps
- ODH
- Open Data Hub
- OpenShift
- OpenShift Data Science
- Python
- PyTorch
- Red Hat
- S2i
- Source-to-image
- Spark
- TensorFlow
Fellow Red Hatters Steven Huels and Sherard Griffin describe how the Open Data Hub meta-project grew from solving practical CI/CD build challenges to where it is today – providing an integrated blueprint stitching together over 20 open source AI tools for running large and distributed AI workloads on OpenShift. Part 1 of a 2 part […]
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Activation Functions – Deep Learning Dictionary
-
Frank
- June 28, 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 activation functions within artificial neural networks?
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