Video Directory
MLOPs World & Generative AI World 2023 - Oct. 26th Sessions
Is It Too Much to Ask for A Stable Baseline?
Getting Higher ROI on MLOps Initiatives
GenAI: Lessons Learned
Supercharging Search with LLMs
Generative AI: The Open Source Way
Chat with MLOps World: Engineering an LLM Application
Train, and Deploy Models, Lightning Fast
ML Platform Beyond Kaggle Paradigm
Data Versioning in Generative AI: A Pathway to Cost-Effective ML
Creating the World's Premier Biological Foundation Model
Goose, Chewbacca, & AI: Safely Flying the Generative AI Skies
The Coming Nuclear Winter for AI Chip Companies
LLM, from Playgrounds to Production-ready Pipelines
Dreambooth - Stable Diffusion for Custom Images
Data @ League
MemeGPT: Creating a Large Language Model to Generate Memes
Building an End-To-End Mlo Ps Pipleline
Evolved Structures: Generative Design and Digital Manufacturing at NASA
Introduction to LangChain and Retrieval Augmented Generation (RAG)
Solution for Black Box AI
Oracles and Worker Bees: The future of AI models
LanceDB: A Unified Storage Layer for Vector Search, Analytics, and Model Training
Read-Write Separation in Fennel
Protecto - Enabling AI with Security and Trust
Airflow: Where data engineers and ML engineers meet
Feature Stores ≠ Storage
How NOT to Get ML Models into Production To Maybe there's a Path
Retrieval Augmented Generation (RAG) with LangChain" "ChatGPT for Your Data" with Open-Source Tools (Part 2)
MLOps isn't that hard Modular Stack with Open-Source Tools
MLOPs World & Generative AI World 2023 - Oct. 25th Sessions
Building the NeurIPS LLM Efficiency Challenge Leaderboard
LLMs from Hallucinations to Relevant Responses
How to Finetune Your LLMs and Evaluate Performance
Operationalizing Data-Centric: AI Practical Tools to Quickly Improve ML Datasets
LLMs Big Data and Audio: Breaching an untapped Gold Mine
Overcoming the Challenges of Building GenAI Apps
Training LLMs: Lessons from the Trenches
How Many Labelled Examples Do You Need for a BERT-sized Model to Beat GPT4 on Predictive Tasks
Hyper-Scaling Real-Time Personalization with Privacy via On-Device Computing
Your AI Applications Need Guardrails: Here's How To Build Them
Building Your LLM Factory
Scouter Models for Concept Drift Detection
Retrieval Augmented Generation (RAG) with LangChain" "ChatGPT for Your Data" with Open-Source Tools (Part 1)
From Analytics to AI: How Gen AI Can Unlock Data Insights & Transform Decision-Making
Fine-Tune LLMs or Integrate 3rd party APIs A Financial Case-Study
Production ML Serving & Monitoring with Kubernetes
Business Panel: GenAI Use-cases Across Industry Verticals. Early Trends & ROI
From Prototype to Product: Rapid iteration and ML model deployment at Dropbox
Creative Serving: A tour of Model Serving Strategies
Low-latency Model Inference in Finance - A close look at Seldon V2
MLOPs On Highly Sensitive Data
From Model T to Machine Learning: A Glimpse into Ford's MLOps and Hybrid Infrastructure Strategy
Evolution of ML Training and Serving Infrastructure @ Pinterest Ads
Evaluation Techniques for Large Language Models
Building an MLOps Team
How Do You Scale to Billions of Fine-Tuned LLMs
Supercharging Recommender Systems: Unleashing the Power of Distributed Model Training
MLOps World 2023 Conference Talk
Reproducibility and Data version control for LangChain and LLM/OpenAI Models
MLOps World 2022 Conference Talks
Transformative Power of ML in the Real World
Don't Fear Compliance Requirements & Audits Implementing SecMLOps at Every Stage of the Pipeline
One Cluster to Rule Them All ML on the Cloud Using Ray on Kubernetes and AWS
How MLOps Tools Will Need to Adapt to Responsible and Ethical Al Stay Ahead of the Curve
Low latency Neural Network Inference for ML Ranking Applications Yelp Case Study
Eliminating Al Risk, One Model Failure at a Time
Top 5 Lessons Learned in Helping Organizations Adopt MLOps Practices
Scotiabank's Path Towards Accelerated Analytics Through GCP
Robustness and Security for Al and the Dangerous Dismissal of Edge Cases
A Framework for a Successful Continuous Training Strategy
How to Conquer Data Drift & Prevent Stale Models in Production using DVC
Managing Human in the Loop Systems Without Burning Out Your Engineers
SLA Aware Machine Learning Inference Serving on Serverless Computing Platforms
Wild Wild Tests: Testing Recommender Systems in the Wild
Feature Engineering Made Simple
Machine Learning Infrastructure at Meta Scale
The Future of Feature Stores
MLOps for Deep Learning
Shopify's ML Platform Journey Using Open Source Tools Case study building Merlin & AMA
MLOps for Fairness: Creating Comprehensive Fairness Workflows
Managing a Data Science Team During the Great Resignation
Supporting Sales Forecasting at Scale for Canada's Largest Grocery Store
Cutting-edge NLP, Large Language Models, and Their Implications For Products and Research
The Critical Things You Have to Build to Transform Your Company to be ML Driven
Panel: What Every Product Manager Delivering Al Solutions Should Know
What Do Engineers Not Get About Working with Data Scientists
MLOps at Rovio for Personalization Self Service Reinforcement Learning in Production
A Guide for Start ups; How to Scale a PoC to Production System and Not Go Up in Smoke
CyclOps - A framework for Data Extraction, Model Evaluation and Drift Detection for Clinical Use
A Guide to Building a Continuous MLOps Stack
Al in Robotics, Manufacturing, and Media How Good Practices Can Shape the Future
It's All About The Data Continuously Improve ML Models, The Data-Centric Way
Understanding Foundation Models a New Paradigm for Building and Productizing Al Systems
Hands on: A Beginner Friendly Crash Course to Kubernetes
Solving MLOps From First Principles A Framework to Reduce Complexity MLOps World Machine Learning in Production
Panel: Embedding Diversity and Fairness Into Your Model Governance
Building Production ML Monitoring from Scratch Live Coding Session
How We Reduced 83% of ML Computing Cost on 100+ ML Projects
Becoming An ML Platform Power Builder Powered by ML Observability
Introduction to Model Deployment with Ray Serve
UnionML: A Microframework for Building Machine Learning Applications
Concretes Guidelines to Improve ML Model Quality, Based on Future ISO Certifications
A GitOps Approach to Machine Learning
Building Real Time ML Features with a Feature Platform
MLOps World 2022 Virtual Workshops
Supercharging MLOps with the Petuum Platform
Scaling ML Embedding Models to Serve a Billion Queries
MLOps is Just HPC in Disguise A Real World, No Nonsense Guide to Upgrading Your Workflow
Critical Use of MLOps in Finance Using Cloud-Managed ML Services That Scale
Building Real-Time ML Features with Feast, Spark, Redis and Kafka
Trustworthy Al for MLOps
What's in the Box: Automatic ML Model Containerization
WarpDrive: Orders of Magnitude Faster Multi-Agent Deep RL on a GPU
Taking MLOps 0-60: How to Version Control, Unify Data and Manage Code Lifecycles
Scale and Accelerate the Distributed Model Training in Kubernetes Cluster
Production ML for Mission Critical Applications
Personalized Recommendations and Search with Retrieval and Ranking at scale on Hopsworks
MLOps Beyond Training: Simplifying and Automating the Operational Pipeline
Machine Learning Monitoring in Production: Lessons learned from 30+ Use Cases
Lessons Learned from DAG based Workflow Orchestration
Leaner, Greener and Faster Pytorch Inference with Quantization
How to Treat Your Data Platform Like a Product 5 Key Best Practices
How to MLEM Your Models to Production
Generalizing Diversity Machine Learning Operationalization for Pharma Research
Deploying and Managing Machine Learning Models at Scale: A Hands-On Workshop with Seldon
Defending Against Decision Degradation with Full Spectrum Model Monitoring Case Study and AMA
Automated Machine Learning Tuning with FLAML
Accelerating Transformers with Hugging Face Optimum and Infinity
A Zero Downtime Set up for Models: How and Why
Parallelizing Your ETL with Dask on Kubeflow
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