Begin your AI transformation journey here! cnvrg.io AI Blueprints are customizable pre-trained models to help you apply AI to your business needs more quickly. In these 2 hour workshops, you’ll use our Blueprints and your own data to see how you can apply AI to solve real-world business problems. These instructor-lead virtual training sessions are hands-on, so you’ll walk away with the building blocks to create an end to end ML pipeline. Network with your AI peers and instructors to share ideas that you can implement right away.
Discover the advantages of a multi-cloud environment and learn how to make it happen in reality. Learn strategies and tips to move between clouds and run a pipeline across multiple cloud providers using cnvrg.io, while having a centralized control plane and MLOps tooling.
This webinar will explore the latest developments and trends in AI technology, with a focus on the impact of advanced language models such as ChatGPT, and discuss the steps organizations can take to prepare for the next generation of AI solutions.
This webinar will take you through a step by step process of building your own stable diffusion application using OpenVINO, and experience the optimized performance of the latest generation of Intel® Xeon® Scalable processors in action.
In this webinar you will learn how to utilize Kubernetes for distributed workloads to easily scale your ML models and automate the management of workload performance.
In this webinar you will learn practical tools, architecture and skills needed to shorten the time to market for AI initiatives in your organization.
In this webinar you will learn techniques for implementing and automating continuous integration (CI), continuous delivery (CD), and continuous training (CT) for machine learning systems. You will get leading strategies from a cnvrg.io AI expert on how to monitor and retrain models in production, and ensure your models run smoothly in a production environment.
Chatbots can help businesses communicate with their customers quickly while also understanding their needs and responding accordingly. Chatbots, also called virtual agents, are a great way to provide a great streamlined customer experience.
Create a recommender that finds patterns in consumer behavior data to identify products or services that can be cross-sold.
Get certified in building your own text detection application in this hands-on 2 hour workshop.
Use our Sentiment Blueprint to analyze social media feeds and understand what customers are saying about your brand.
Habana Gaudi processors enable high-performance AI/Deep Learning (DL) training compute. In this workshop, we’ll create a Blueprint that can understand human language. April 4, 0800 PST, 1600 GMT
Learn How to use cnvrg.io Metacloud training pipelines with Habana Gaudi AI processors
Learn How to Run Efficient Distributed Training on CPU/GPU A1-Ready Servers
Learn how to build an end to end NLP pipeline with BERT in PyTorch.
Learn how Seagate Technology is using machine learning to advance their manufacturing capabilities
Learn best practices for building an end-to-end workflow for Autonomous Driving applications with experts from Dell and cnvrg.io.
Learn how to get started with MLOps & solve data science challenges
Learn How to increase utilization with MLOps visualization dashboards
Learn to leverage NVIDIA Multi-Instance GPU for your ML workloads.
Learn how to optimize distributed training for multi-node and multi GPU training to maximize performance.
Learn how Playtika – a leader in the gaming-entertainment industry – deployed large-scale and real-time predictions while increasing successful model throughput by up to 50% and reduced latency and errors to 0 with streaming endpoints on cnvrg.io.
In this webinar cnvrg.io CEO, Yochay Ettun will host a special guest from NVIDIA, Sr. Product Manager for NVIDIA DGX systems, Michael Balint, and discuss how to optimize the use of any NVIDIA DGX and NVIDIA GPU asset both on-prem or in the cloud with the cnvrg.io machine learning platform.
Join our hands-on workshop series and deep dive into machine learning and deep learning with cnvrg.io
Join CEO, Yochay Ettun, as he walks you through the main components of the cnvrg.io platform so you can begin rapid experimentation, building ML pipelines, and deploying your models to production in one click. Download the recording and get a free trial!
Deployment is a major challenge facing enterprise success in AI. On premise solutions face specific difficulties that we will discuss in this webinar. We will discuss best practices of enterprise machine learning, and how to get more of your models to production. While there are many solutions that help streamline the ML deployment process for cloud enterprises, few solutions exist for on premise enterprises
Join this live webinar to examine best practices for building a machine learning pipeline that enables quick iteration, deployment and CI/CD.
Learn enterprise-level strategies for monitoring machine learning bias in a live webinar. Join data science experts as we seek ways to prevent bias in your ML models.
This webinar will offer strategies on how to design your machine learning pipelines for a more efficient, integrated and automated process.
In this webinar, we’ll discuss how to build a system to monitor your machine learning model in production on Kubernetes. You’ll learn to keep track of different models and their model performance over time, and how to set up custom alerts for your models.
Join cnvrg.io and special guest Scale AI in a webinar on continual learning with human-in-the-lop. By creating a continuous feedback loop between human and machines, machine learning models become smarter, more confident, and more accurate over time.
In this webinar, we’ll discuss core practices in MLOps that will help data science teams scale to the enterprise level.
Using CI/CD for machine learning applications creates a truly end-to-end pipeline that closes the feedback loop at every step of the way, and maintains high performing ML models. Join CEO of cnvrg.io Yochay Ettun as he brings you through how to create a CI/CD pipeline for machine learning, and set up continuous deployment in just one click.
Follow cnvrg.io CTO Leah Kolben in a step-by-step tutorial on how to deploy and connect your machine learning models with Kubernetes. In just 30 minutes she’ll show you how to get your model in production and running smoothly for your end-user in a real-time example.
This webinar will instruct data scientists and machine learning engineers on how to build manage and deploy auto-adaptive machine learning models in production. Using state of the art Kubernetes infrastructure, we’ll show you how to automatically track and manage your auto-adaptive machine learning models while in production.
oin CTO of cnvrg.io Leah Kolben as she brings you through a step-by-step tutorial on how to run Spark on Kubernetes. You’ll have your Spark up and running on Kubernetes in just 30 minutes. Learn how you can scale Spark using Kubernetes. Thanks to the new native integration between Apache Spark’s and Kubernetes, scaling data processing has never been easier.
This workshop will give you the proper tools and tactics to manage the entire lifecycle of your machine learning projects, from research to exploration to development and production. Yochay will go over the different roles and responsibilities of a data science team and how to better collaborate on machine learning projects.
Join CTO of cnvrg.io Leah Kolben in a live workshop. Leah will walk you through each step to set up your Kubernetes cluster, so you can run Spark, TensorFlow, and any ML framework instantly.
In this webinar, data science expert and CEO of cnvrg.io Yochay Ettun discusses continual learning in production. This webinar examines continual learning, and will help you apply continual learning into your production models using tools like Tensorflow, Kubernetes, and cnvrg.io.
In this webinar, data science expert Yochay Ettun will present a step-by-step use case so you can build your own AutoML computer vision pipelines. Yochay will go through the essentials for research, deployment and training using Keras, PyTorch and TensorFlow.