Story Tag: machine-learning

Stories Tag: machine-learning

Persistent Storage for Kubernetes | by Afzal Muhammad | Oct, 2020 | Medium

admin 1 day ago in

Deploy Portworx on Red Hat OpenShift Container Platform In today’s digital era, the value of containerized application is unquestionable. It’s a paradigm shift in application development and it’s a move in adopting DevOps and cloud native architecture for successful digital transformation. Due to this, Kubernetes (K8) has become a mainstream and de-facto standard for container orchestration. Kubernetes has lot of moving parts, however, in this…

Installing Kubeflow on macOS with MicroK8s | by Dan Siwiec | Dan On Coding | Oct, 2020 | Medium

admin 2 days ago in

Simple steps for getting Kubeflow off the ground on your Mac (hint: it’s not ‘helm install…’) MicroK8s is a fully-compliant mini Kubernetes implementation. Thanks to its tiny footprint, it is perfectly suited for local installation. We’ll install it with brew: Once it’s installed on your machine, we can provision a local cluster this way: The additional –cpu and –mem parameters increase the CPU count and…

DKube: Kubeflow Implementation On-Prem or AWS/GCP/Azure | by Ajay Tyagi | Oct, 2020 | Medium

admin 5 days ago in

Deploying Kubeflow on AWS, GCP, Azure or on-prem: It is a lot more than just downloading and installing open source Kubeflow Can your Kubeflow implementation work as shown in the graphic below? Over the past two plus years Kubeflow has come along a long way in bringing together many open source innovations to implement a cost effective AI/ML platform. These include KF Pipelines, KF Serving,…

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

admin 1 week 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…

Embracing the journey from a world of containers to Virtual Machines. | by Kalyan Gande | Oct, 2020 | Medium

admin 3 weeks ago in

Embracing the journey from a world of containers to Virtual Machines. A small intro about me, I’m Kalyan, working as a Data Science Engineer in an MNC. I’m a tech enthu. You can ask me about smartphones, software, electric cars, cameras, gaming consoles, smartphone gimbals. I have started my journey as Software Engineer as a fresher in Virtusa. First two months were boring. Then things…

Deploying a ML service to Azure Container Service (AKS) | by Sanajit Ghosh | Oct, 2020 | Medium

admin 3 weeks ago in

In this setup we need to create two resource groups using Machine Learning workbench CLI and Azure portal itself. At the end of deployment, we are going to the follow the resource structure as given below. The first resource group SGresourcegrpML (maintaining a naming convention is preferred as there are too many resource items) contains the account, model management and storage which are named accordingly….

Install Kubeflow on Minikube. Here I followed Kubeflow official… | by Sazzad Abdul Hasib | Oct, 2020 | Medium

admin 3 weeks ago in

Here I followed Kubeflow official documentation Follow the above link to install The Kubernetes cluster must meet the following minimum requirements: Your cluster must include at least one worker node with a minimum of: Check Kubeflow by check the pod status using kubectl get pod -n ubectl get pod -n kubeflowkubeflow { “exec-opts”: [“native.cgroupdriver=systemd”], “log-driver”: “json-file”, “log-opts”: { “max-size”: “100m” }, “storage-driver”: “overlay2”} into /etc/docker/daemon.json…

Building ML Componentes on Kubernetes | by Santiago Cotto | Oct, 2020 | Medium

admin 4 weeks ago in

Hello! Here at KONA, everything we build is a component, and that concept has changed us, the way we work, and our product strategy! Each time we discuss a product feature or a new product, we first think of what we need and what components we can re-use from what we already have in our Catalog. Every project or feature starts with a Jupyter notebook…

Kubeflow is More Accessible than Ever | by Dimitris Poulopoulos | Oct, 2020 | Towards Data Science

admin 4 weeks ago in

A Machine Learning project usually consists of multiple, interconnected steps: data acquisition, data processing, data modelling, fine-tuning, testing etc. Each of these steps can be a separate process, running at its own cadence, with clearly defined inputs and outputs. Thus, data scientists and ML engineers tend to think these projects like pipelines. Kubeflow Pipelines, a component of Kubeflow, are here to address this design pattern….