Story Tag: deep-learning

Stories Tag: deep-learning

Kubeflow: Simplified, Extended and Operationalized | by yaron haviv | Nov, 2020 | Towards Data Science

admin 3 months ago in

The success and growth of companies can be deeply intertwined with the technologies they use in their tech stack. Nowhere is this more apparent than in the case of developing ML pipelines. The nature of delivering robust ML models and data pipelines to production is a complex business. Every data science team is faced with the same limitations and constraints, regardless of the scope of…

Parallel Hyperparameter Tuning With Optuna and Kubeflow Pipelines | by Masaki Kozuki | Optuna | Nov, 2020 | Medium

admin 4 months ago in

This entry is a translation of the Japanese-language blog post originally authored by Mr. Masao Tsukiyama of Mobility Technologies Co., Ltd. The Optuna community would like to thank Mr. Tsukiyama for permitting us to post this translation.Disclaimer: All the slides and videos are in Japanese language. Hi there. This is Masao Tsukiyama of ML engineering group 1 of AI technology development department of Mobility Technologies…

Combining multiple deep learning models for production scale license plate processing pipelines | by Onepanel | Oct, 2020 | Medium

admin 4 months ago in

As deep learning models are getting more accurate in a myriad of tasks in computer vision and natural language processing, more and more companies are adopting these new more accurate methods for various business use cases. Since most of these deep learning models are compute-intensive, it becomes increasingly difficult to manage these systems as more and more users use these systems. That is why there…

How to Implement Alluxio in High-Performance Distributed Deep Learning Model Training Scenarios | Data Driven Investor

admin 6 months ago in

By Che Yang (Senior Technical Expert at Alibaba Cloud) and Gu Rong (Research Associate at Nanjing University and Core Developer of Alluxio) In recent years, artificial intelligence (AI) technologies such as deep learning have rapidly developed and are being used in a wide range of industries. With the widespread application of deep learning, an increasing number of fields are demanding efficient and convenient AI model…

How Alluxio Simplifies Running the PyTorch Framework on HDFS Using the Kubernetes Platform | Medium

admin 6 months ago in

By Biran Google’s TensorFlow and Facebook’s PyTorch are two popular deep learning frameworks in the community. Although PyTorch is relatively new, it has developed rapidly due to its developer-friendly experience. However, PyTorch disallows directly training models in Hadoop Distributed File System (HDFS) by default. This makes it difficult for many users who store datasets in HDFS. Therefore, for training models, it necessitates users to export…

Serve Your Pytorch Models on CPU or NVIDIA Gpu Leveraging Kubeflow kfserving using Pytorch Server Custom Image | by Kaustav...

admin 7 months ago in

Kubeflow comes with a line of lineup of model serving. We are goung to discuss about the kfserving module and how it can be utilized to serve a Pytorch model which can be auto-scaled,or zero scaled with the resource utilizaion changing dynamics. THE BIGGEST CHALLENGE!!! The biggest challenge is the Kubeflow Docs which does not provide a clear picture on how one can run a…

Deep Learning at Alibaba Cloud with Alluxio — Running PyTorch on HDFS

admin 8 months ago in

Google’s TensorFlow and Facebook’s PyTorch are two Deep Learning frameworks that have been popular with the open source community. Although PyTorch is still a relatively new framework, many developers have successfully adopted it due to its ease of use. By default, PyTorch does not support Deep Learning model training directly in HDFS, which brings challenges to users who store data sets in HDFS. These users…

🚀 Watch Me Scale: A Story of Productivity in Deep Learning with Metaflow and Kubernetes

admin 10 months ago in

Prologue I am software engineer who has been building software for over 6 years. I came to Arizona State University in 2019 to study Artificial Intelligence and Machine Learning. In my journey through Deep learning and AI, I encountered a life saving library which greatly improved productivity of research. This blog post entails my experience of Metaflow through the lens of some projects I did…