Adversarial Autoencoders (with Pytorch)
Learn how to build and run an adversarial autoencoder using PyTorch. Solve the problem of unsupervised learning in machine learning.
Writing CNNs from Scratch in PyTorch
One of the best ways to learn about convolutional neural networks (CNNs) is to write one from scratch! In this post we look to use PyTorch and the CIFAR-10 dataset to create a new neural network.
Unlock the Power of AI/ML and Managed OpenSearch
As AI/ML continues to dominate the tech landscape, new tools emerge to streamline development and improve efficiency. This session explores how OpenSearch projects can benefit from AI/ML, delivering smarter, faster solutions.
Real-Time translated speech pipeline with Whisper and Soprano
‘In this tutorial, we walk through and demonstrate our pipeline for realtime speech translation into English using Deep Learning.’
Predicting Molecular Structures with AlphaFold 2 and 3
‘ Learn about the evolution of AlphaFold and how to deploy AlphaFold 2 and 3 on GPU cloud servers.’
Getting Started with 1-Click Models on GPU Droplets – A Guide to Llama 3.1 with Hugging Face
In this article, we’ll guide you on getting started with the One-Click Models on GPU Droplets, and provide an in-depth look at Llama 3.1.
Como Instalar e Utilizar o TensorFlow no Ubuntu 16.04
O TensorFlow é um software open-source para machine learning criado pelo Google para treinar redes neurais. As redes neurais do TensorFlow são expressas na forma de [grafos de fluxo de dados com…
Prompt Caching Explained
Learn what prompt caching is, how it works in LLM workflows, and how it improves performance, reduces latency, and lowers inference costs.
Principal Component Analysis (PCA) in Machine Learning
Learn Principal Component Analysis (PCA) in machine learning, learn how it reduces data dimensionality to improve model performance and visualization.
Object Detection Using Mask R-CNN with TensorFlow 1.14 and Keras (TENSORFLOW-2-0)
Learn how to perform object detection and instance segmentation using Mask R-CNN with TensorFlow 1.14 and Keras.