Topics: AI | Data Science | Data Visualization | Deep Learning | Machine Learning | NLP | Python | R | Statistics

About Kevin Vu

Kevin Vu manages Exxact Corp blog and works with many of its talented authors who write about different aspects of Deep Learning.

Kevin Vu Posts (53)

  • Federated Learning: Collaborative Machine Learning with a Tutorial on How to Get Started - 21 Dec 2021
    Read on to learn more about the intricacies of federated learning and what it can do for machine learning on sensitive data.
  • What Are NVIDIA NGC Containers & How to Get Started Using Them - 15 Nov 2021
    NVIDIA, the pioneer in the GPU technologies and deep learning revolution, has come up with an excellent catalog of specialized containers that they call NGC Collections. In this article, we explore their basic usage and some variations.
  • 7 Top Open Source Datasets to Train Natural Language Processing (NLP) & Text Models - 08 Nov 2021
    With a lot of excitement and research around NLP, there are growing opportunities to apply these technologies to real-world scenarios. It's not trivial to become familiar with NLP and these open-source data sets can help you increase your skills.
  • Advanced PyTorch Lightning with TorchMetrics and Lightning Flash - 01 Nov 2021
    In this tutorial we will be diving deeper into two additional tools you should be using: TorchMetrics and Lightning Flash. TorchMetrics unsurprisingly provides a modular approach to define and track useful metrics across batches and devices, while Lightning Flash offers a suite of functionality facilitating more efficient transfer learning and data handling, and a recipe book of state-of-the-art approaches to typical deep learning problems.
  • Getting Started with PyTorch Lightning - 26 Oct 2021
    As a library designed for production research, PyTorch Lightning streamlines hardware support and distributed training as well, and we’ll show how easy it is to move training to a GPU toward the end.
  • AutoML: An Introduction Using Auto-Sklearn and Auto-PyTorch - 11 Oct 2021
    AutoML is a broad category of techniques and tools for applying automated search to your automated search and learning to your learning. In addition to Auto-Sklearn, the Freiburg-Hannover AutoML group has also developed an Auto-PyTorch library. We’ll use both of these as our entry point into AutoML in the following simple tutorial.
  • Silver BlogIntroduction to PyTorch Lightning - 04 Oct 2021
    PyTorch Lightning is a high-level programming layer built on top of PyTorch. It makes building and training models faster, easier, and more reliable.
  • Silver BlogSurpassing Trillion Parameters and GPT-3 with Switch Transformers – a path to AGI? - 01 Oct 2021
    Ever larger models churning on increasingly faster machines suggest a potential path toward smarter AI, such as with the massive GPT-3 language model. However, new, more lean, approaches are being conceived and explored that may rival these super-models, which could lead to a future with more efficient implementations of advanced AI-driven systems.
  • Computer Vision in Agriculture - 27 Sep 2021
    Deep learning isn’t just for placing ads or identifying cats anymore. Instead, a slew of young startups have started to incorporate the advances in computer vision made possible through larger and larger neural networks to real working robots in the fields.
  • A Breakdown of Deep Learning Frameworks - 23 Sep 2021
    Deep Learning continues to evolve as one of the most powerful techniques in the AI toolbox. Many software packages exist today to support the development of models, and we highlight important options available with key qualities and differentiators to help you select the most appropriate for your needs.

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