Dropout is a simple and powerful regularization technique for neural networks and deep learning models. In this post, you will discover the Dropout regularization technique and how to apply it to your models in PyTorch models. After reading this post, you will know: How… Read More »Using Dropout Regularization in PyTorch Models Adrian Tam MachineLearningMastery.com
RAID (redundant array of independent disks) is a way of combining multiple physical disk drives into one logical unit, which can increase performance, redundancy, and capacity depending on the RAID level used. In this blog post, we will discuss the different RAID levels, their… Read More »Understanding the Different Raid Levels: An Introduction Seb Programmathically
Posted by Parker Riley, Software Engineer, and Jan Botha, Research Scientist, Google Research Many languages spoken worldwide cover numerous regional varieties (sometimes called dialects), such as Brazilian and European Portuguese or Mainland and Taiwan Mandarin Chinese. Although such varieties are often mutually intelligible to their… Read More »FRMT: A benchmark for few-shot region-aware machine translation Google AI Google AI Blog
Modern model pre-training often calls for larger cluster deployment to reduce time and cost. At the server level, such training workloads demand faster compute and increased memory allocation. As models grow to hundreds of billions of parameters, they require a distributed training mechanism that… Read More »Scaling Large Language Model (LLM) training with Amazon EC2 Trn1 UltraClusters K.C. Tung AWS Machine Learning Blog
It’s been well publicized that Google’s Bard made some factual errors when it was demoed, and Google paid for these mistakes with a significant drop in their stock price. What didn’t receive as much news coverage (though in the last few days, it’s been… Read More »Sydney and the Bard Mike Loukides AI & ML – Radar
Posted by the TensorFlow Datasets team Datasets landscape has changed a lot since TensorFlow Datasets (TFDS) was introduced about 4 years ago: TFDS made sharing or re-using a dataset significantly easier, and transformed the datasets landscape by inspiring other ML tools, libraries and services.… Read More »TensorFlow Datasets is turning 4! noreply@blogger.com (TensorFlow Blog) The TensorFlow Blog
Enterprises across the globe are looking to utilize multiple data sources to implement a unified search experience for their employees and end customers. Considering the large volume of data that needs to be examined and indexed, the retrieval speed, solution scalability, and search performance… Read More »New expanded data format support in Amazon Kendra Rishabh Yadav AWS Machine Learning Blog
The video above represents one of the first times that a pangolin, one of the world’s most critically endangered species, was detected in real time using artificial intelligence. A U.K.-based nonprofit called Conservation AI made this possible with the help of NVIDIA technology. Such… Read More »UK’s Conservation AI Makes Huge Leap Detecting Threats to Endangered Species Across the Globe Angie Lee – Archives Page 1 | NVIDIA Blog
The loss metric is very important for neural networks. As all machine learning models are one optimization problem or another, the loss is the objective function to minimize. In neural networks, the optimization is done with gradient descent and backpropagation. But what are loss… Read More »Loss Functions in PyTorch Models Adrian Tam MachineLearningMastery.com
Amazon SageMaker JumpStart is the machine learning (ML) hub of SageMaker that offers over 350 built-in algorithms, pre-trained models, and pre-built solution templates to help you get started with ML fast. JumpStart provides one-click access to a wide variety of pre-trained models for common… Read More »Implementing MLOps practices with Amazon SageMaker JumpStart pre-trained models Vivek Gangasani AWS Machine Learning Blog