Series: Gradient Descent with Python Implementing Gradient Descent in Python, Part 4: Using Any Number of Neurons In this tutorial we extend our implementation of gradient descent to work with a single hidden layer with any number of neurons. Part 4 is divided into two sections. In the first we
Gradient Introducing Gradient Public Profiles 📣 Public profiles in Gradient are designed to make it easier to publish and discover machine learning projects on the Gradient platform. As always, we are eager to hear your feedback. Claim your username
Announcement Introducing Gradient Community Notebooks: Easily Run ML Notebooks on Free GPUs Whether you’re a machine learning enthusiast, researcher, or professional, setting up and managing your work environment can be a complex and distracting process. Even when you're done dealing with installation and version
interview DeepFake Faceoff w/ Dr. Fakenstein & CtrlShiftFace Deepfake technology is unlocking a new era of media production. As with all technologies, both positive and harmful use cases exist. As ethical technologists, we aspire to push the limits of what is
Announcement Introducing the next iteration of Gradient: Run on-prem, in your cloud, or hybrid Update: This launch was featured in TechCrunch Over the last few years, we've fielded countless requests to run Gradient, our MLOps SaaS platform, on existing infrastructure, ranging from local bare metal servers, to
Tutorial Neural Machine Translation with TensorFlow If you are a fan of Google translate or some other translation service, do you ever wonder how these programs are able to make spot-on translations from one language to another on par
Series: Gradient Descent with Python Implementing Gradient Descent in Python, Part 3: Adding a Hidden Layer Hello again in the series of tutorials for implementing a generic gradient descent (GD) algorithm in Python for optimizing parameters of artificial neural network (ANN) in the backpropagation phase. The GD implementation will
Tutorial Unpaired Image to Image Translation with CycleGAN Yann LeCun, director of AI research at Facebook and Professor at NYU described Generative Adversarial Networks, GANs as the most interesting idea in Machine Learning in the last 10 years. Since the invention
Gradient New Gradient Python SDK Build out complex end-to-end machine learning pipelines with the new Gradient Python SDK.
Series: Gradient Descent with Python Implementing Gradient Descent in Python, Part 2: Extending for Any Number of Inputs Hello again in the series of tutorials for implementing a generic gradient descent (GD) algorithm in Python for optimizing parameters of artificial neural network (ANN) in the backpropagation phase. The GD implementation will
Tutorial TensorFlow 2.0 in Action TensorFlow is one of the most popular frameworks used for deep learning projects and is approaching a major new release- TensorFlow 2.0. Luckily, we don't have to wait for the official release.
Advanced Technologies Group Move Quickly, Think Deeply: How Research Is Done @ Paperspace ATG The Advanced Technologies Group is an R&D-focused team here at Paperspace, comprising ML Engineers and Researchers. As a group, we're interested in exploring advanced topics in deep learning, data engineering, computer
Series: Gradient Descent with Python Implementing Gradient Descent in Python, Part 1: The Forward and Backward Pass Through a series of tutorials, the gradient descent (GD) algorithm will be implemented from scratch in Python for optimizing parameters of artificial neural network (ANN) in the backpropagation phase. The GD implementation will
Deep Learning 6 Interesting Deep Learning Applications for NLP Read on to discover deep learning methods are being applied in the field of natural language processing, achieving state-of-the-art results for most language problems.
Deep Learning Building a State of the Art Bacterial Classifier with Paperspace Gradient and Fast.ai One of the great promises of Deep Learning is its applicability in a wide variety of complex tasks. Recent years have seen an explosion in the number of fields Deep Learning has seen
Train ML Models on Free Cloud GPUs ⚡ When we started Paperspace back in 2014, our mission was to make cloud GPU resources more accessible and less expensive for everyone. Since inception, we have continued to offer a wide variety of
pytorch PyTorch 101, Part 5: Understanding Hooks In this post, we cover debugging and Visualisation in PyTorch. We go over PyTorch hooks and how to use them to debug our backpass, visualise activations and modify gradients.
Tutorial PyTorch 101, Part 4: Memory Management and Using Multiple GPUs This article covers PyTorch's advanced GPU management features, including how to multiple GPU's for your network, whether be it data or model parallelism. We conclude with best practises for debugging memory error.
Tutorial PyTorch 101, Part 3: Going Deep with PyTorch In this tutorial, we dig deep into PyTorch's functionality and cover advanced tasks such as using different learning rates, learning rate policies and different weight initialisations etc
pytorch PyTorch 101, Part 2: Building Your First Neural Network In this part, we will implement a neural network to classify CIFAR-10 images. We cover implementing the neural network, data loading pipeline and a decaying learning rate schedule.
Deep Learning PyTorch 101, Part 1: Understanding Graphs, Automatic Differentiation and Autograd In this article, we dive into how PyTorch's Autograd engine performs automatic differentiation.
Tutorial Convert Full ImageNet Pre-trained Model from MXNet to PyTorch Currently there are many available deep learning frameworks for researchers and engineers to implement their desired deep models. Each deep learning framework has its own advantages and disadvantages. For example, TensorFlow has a
Tutorial Detecting and Localizing Pneumonia from Chest X-Ray Scans with PyTorch Over the years, we have seen very powerful models being built to distinguish between objects. These models keep getting better in terms of performance and latency day by day but have we ever
Announcement Multinode/Distributed Training, New GitHub App, and More! Introducing GradientCI, a powerful new way to train, and deploy machine learning models from GitHub. Add superpowers to your ML workflow.
Gradient Gradient° update (2/22/2019) Gradient° has been updated in response to a ton of feedback from the community. Here's a roundup of some of the things we've added recently: New System & Custom Metrics! Now whenever you
