NLP Generating Text Summaries Using GPT-2 on PyTorch with Minimal Training In this article I will discuss an efficient abstractive text summarization approach using GPT-2 on PyTorch with the CNN/Daily Mail dataset.
Updated Terraform Installer, New CLI, and Introducing Managed Private Gradient Clusters We recently launched the Terraform-based Gradient MLOps Installer to let users turn any cloud into a super-powerful machine learning platform. Out of the box the Gradient Installer lets you run
NumPy Nuts and Bolts of NumPy Optimization Part 2: Speed Up K-Means Clustering by 70x In this part we'll see how to speed up an implementation of the k-means clustering algorithm by 70x using NumPy. We cover how to use cProfile to find bottlenecks in the code, and how to address them using vectorization.
Customer Story Building Virtual Worlds with CyberLayerVR Q&A with CyberLayerVR's Founder and CEO Bo Layer, a subject expert in VR, gaming, and machine learning.
NumPy Nuts and Bolts of NumPy Optimization Part 1: Understanding Vectorization and Broadcasting In Part 1 of our series on writing efficient code with NumPy we cover why loops are slow in Python, and how to replace them with vectorized code. We also dig deep into how broadcasting works, along with a few practical examples.
Machine Learning Building a Game-Playing Agent for CoinTex Using the Genetic Algorithm Games can have complex environments, where many different factors contribute to making a decision. An entire area of artificial intelligence is devoted to building game-playing agents that can make the
Python Getting Started with PyPy The Python programming language is an interface that can be implemented in many ways. Some examples include CPython which uses the C language, Jython that is implemented using Java, and
Neural Network Capsule Networks: A Quick Primer Whether you're new to deep learning or a serious researcher, you've surely encountered the term Convolutional Neural Networks. They are one of the most researched and top-performing architectures in the
Computer Vision Attention Mechanisms in Computer Vision Part 1: CBAM This post covers an in-depth analysis of the Convolution Block Attention Module (CBAM) with a short introduction to Visual Attention Mechanisms.
Data Science 2 Books to Strengthen Your Command of Python Machine Learning This post is part of “AI education”, a series of posts that review and explore educational content on data science and machine learning. Mastering machine learning is not easy, even
Coronavirus Fighting Coronavirus with AI, Part 2: Building a CT Scan COVID-19 Classifier Using PyTorch Using PyTorch, we create a COVID-19 classifier that predicts whether a patient is suffering from coronavirus or not, using chest CT scans of different patients.
YOLO How to Improve YOLOv3 YOLO has been a very popular and fast object detection algorithm, but unfortunately not the best-performing. In this article I will highlight simple training heuristics and small architectural changes that can make YOLOv3 perform better than models like Faster R-CNN and Mask R-CNN.
Machine Learning 5 Genetic Algorithm Applications Using PyGAD This tutorial introduces PyGAD, an open-source Python library for implementing the genetic algorithm and training machine learning algorithms. PyGAD supports 19 parameters for customizing the genetic algorithm for various applications.
Deep Learning A Review of Popular Deep Learning Architectures: DenseNet, ResNeXt, MnasNet, and ShuffleNet v2 The aim of this three-part series has been to shed light on the landscape and development of deep learning models that have defined the field and improved our ability to
Customer Story Gradient Health and Paperspace Team Up to Advance Medical Imaging Gradient Health, a medical technology company building an open research platform for medical imaging, has selected Paperspace as its MLOps platform to bring reproducibility and determinism to its machine learning
Customer Story Kando and Paperspace Partner to Bring Advanced Machine Learning to Municipal Systems Monitoring Kando, a technology company providing smart wastewater management solutions to municipal utilities, has integrated Paperspace’s Gradient machine learning platform to bolster its leading Clear Upstream wastewater event monitoring system.
Machine Learning The 11 Best AI & Machine Learning Podcasts to Add to Your Listening Pipeline Add these podcasts to your weekly listening pipeline to learn from top thought leaders and developers about the future of ai and machine learning, as well as innovative use cases and products.
Interviews Generative Art and the Science of Streaming the Collective Consciousness In collaboration with Bitforms Gallery and Small Data Industries, Paperspace spoke with artist Daniel Canogar, whose work "Loom" is being presented as part of a cloud-based, 24/7 stream of generative software-based art.
Deep Learning A Review of Popular Deep Learning Architectures: ResNet, InceptionV3, and SqueezeNet Previously we looked at the field-defining deep learning models from 2012-2014, namely AlexNet, VGG16, and GoogleNet. This period was characterized by large models, long training times, and difficulties carrying over
Paperspace 4K Streaming Lands in the Latest Paperspace Release! We're pleased to announce that the Paperspace native application now supports 4K streaming on all Dedicated GPU virtual machines. Note: 4K streaming is available in the latest version of the
Deep Learning A Review of Popular Deep Learning Architectures: AlexNet, VGG16, and GoogleNet Problems ranging from image recognition to image generation and tagging have benefited greatly from various deep learning (DL) architectural advancements. Understanding the intricacies of different DL models will help you
Tutorial A Guide to Paperspace's Gradient Community Notebooks Gradient Community Notebooks allow users to create, run, and share Jupyter notebooks on free GPUs. In this post Gradient Community Notebooks will be introduced and the steps to get started
Neural Network Neural Architecture Search Part 3: Controllers and Accuracy Predictors In the first part of this series we saw an overview of neural architecture search, including a state of the art review of the literature. In Part 2 we then
Announcement Paperspace Joins NVIDIA DGX Program With Gradient, our developer-first ML platform, the guiding methodology has always been: How can we make developing ML models as easy as building a modern web app? And what tools can we build to enable software developers from different domains to be successful in machine learning and deep learning?
Machine Learning What is MLOps? The machine learning space is arguably one of the most advanced industries in the world and yet, ironically, the way it operates is reminiscent of software development in the '90s.
