Videos
Webinar "dstack – a command-line utility to provision infrastructure for ML workflows" Paid Members Public
Unlike traditional development workflows, ML workflows are difficult to run on a local machine (due to the lack of memory, more CPUs/GPUs, etc). Imagine, if you could run your ML workflows the very same way as you do it locally, but they would run in the cloud. And you
Webinar "Learning through machine learning: how we built a recommendation system from scratch" Paid Members Public
We at Metro.digital have been building data science products for years and have gathered a fair amount of experience, especially in the area of recommendation systems. Over the last few months, my team’s been focusing on an exciting new challenge: building from scratch a machine learning-based recommendation system
Webinar "Vertex AI Pipelines infrastructure with Terraform" Paid Members Public
Vertex AI is a Google Cloud Platform service specified on building, deploying and scaling ML models with with pre-trained and customizable models. It provides tools for every step of the machine learning workflow across different model types and for different levels of machine learning expertise. Like any cloud platform, it
Webinar "Natural Language Processing and Machine Learning in Healthcare" Paid Members Public
There are several significant improvements that the healthcare sector needs. There are countless opportunities to use technology to deliver more accurate, effective, and impactful treatments at precisely the appropriate time in a patient's care, from chronic illnesses and cancer to radiography and risk assessment. Artificial intelligence (AI) is set to
Webinar "The promising role of synthetic data to enable responsible innovation" Paid Members Public
Good quality FAIR data is fundamental for enhancing data reuse. When we discuss data quality in the FAIR context, we often focus on the metadata level quality attributes like accessibility and reuse conditions rather than the semantic ones like imbalances, outliers, and duplicates. In practice, ensuring both the metadata and
Let's build GPT: from scratch, in code, spelled out Paid Members Public
In this video, Andrej Karpathy demonstrates how to build a Generatively Pretrained Transformer (GPT), following the paper "Attention is All You Need" and OpenAI's GPT-2 / GPT-3, and much more. Make sure that you watch at least parts of it!
Webinar "Deploying DL models with Kubernetes and Kubeflow" (EN) Paid Members Public
In this talk, we'll learn about deploying ML models. First, we'll see how to do it with TF-Serving and Kubernetes, and in the second part of the talk, we'll do it with KFServing and Kubeflow.
Webinar "Pachyderm in production: lessons learned" (RU) Paid Members Public
In this talk, we will take a look at yet another MLOps tool - Pachyderm. This tool is gaining in popularity and is unique for some use-cases. The speaker will share the experience of applying Pachyderm to a real-world, BigData NLP project. Most importantly, we will see the hidden limitations
