Git-Based CI-CD for ML
Learn to implement Git-based MLOps for continuous delivery, automating workflows, and enabling collaboration. Explore open-source tools and hosted ML platforms with a live demo on streamlining ML pipelines.
Latency SLOs Done Right - Calculating and Setting Accurate Service Level Objectives
Explore accurate latency SLO calculation methods, including histogram-based approaches, to set mathematically correct quantiles and improve service level objectives for better monitoring and performance management.
Powering Smart Homes at Scale - Challenges and Architecture for IoT Cloud Systems
Explore the challenges and architectural considerations for building a secure, responsive, and scalable IoT cloud connecting millions of smart homes, focusing on performance, security, and system stability.
Containers at Facebook - Advanced Linux, Btrfs, and Systemd Implementation
Explore Facebook's container infrastructure using Linux, Btrfs, and systemd. Learn about advanced file systems, process management, and new kernel features for high-traffic networks.
How to Train a Deep Learning Model Using Docker
Learn to train deep learning models using Docker, NVIDIA runtimes, and PyTorch for melanoma classification on a single GPU, with practical code implementation and troubleshooting tips.
Dockerizing the Skin Cancer Detection Web Application
Learn to containerize a skin cancer detection web app using Docker, enhancing deployment and scalability of machine learning projects.
Productionizing Real-time Serving with MLflow
Explore production-grade MLflow serving: containerization, custom middlewares, monitoring, logging, and performance optimization for high-scale deployment of machine learning models as REST API endpoints.
Taking Machine Learning to Production with MLflow - New Features and Best Practices
Explore MLflow's latest features for productionizing machine learning, including model management, CI/CD, data schemas, and integration with PyTorch for seamless deployment and operation of ML applications.
Productionizing Machine Learning Pipelines with Databricks and Azure ML
Jumpstart ML projects with Databricks and Azure ML. Learn to build, track, and deploy production-ready pipelines using tools like MLflow, TensorFlow, and PyTorch for efficient, reproducible data science workflows.
The Killer Feature Store - Orchestrating Spark ML Pipelines and MLflow for Production
Explore feature store implementation as an orchestration engine for ML pipeline stages using Spark and MLflow, focusing on deployment management, A/B testing, discovery, and governance.
Productionalizing Models through CI/CD Design with MLflow
Explore MLflow integration with CI/CD for streamlined model deployment. Learn to design and implement automated pipelines using the model registry, enhancing efficiency in machine learning workflows.
Delivery of Deep Transformer NLP Models Using MLflow and AWS SageMaker for Enterprise AI
Learn to deploy deep transformer NLP models using MLflow and AWS SageMaker for enterprise AI, covering the full machine learning lifecycle and CI/CD pipelines for production-quality implementation.
Using Docker Images in Production - Databricks Case Study
Learn how Condé Nast evolved Spire, their user segmentation service, from notebooks to Docker images on Databricks clusters. Explore the streamlined deployment workflow, challenges faced, and solutions implemented.
Consolidating MLOps at Schiphol Airport Using MLFlow
Explore how Schiphol Airport leverages MLFlow for rapid iteration, deployment, and monitoring of mission-critical machine learning models, enabling multiple weekly releases and efficient adaptation to changing dynamics.
Observability: Understanding and Implementing the Three Pillars - Monitoring, Tracing, and Logging
Explore observability practices, tools, and culture to enhance system monitoring, troubleshooting, and performance. Learn to implement effective logging, tracing, and alerting for improved incident response and client communication.
Training a GAN from Your Own Images - StyleGAN2 ADA
Learn to create custom GANs using your own images, from setup to training. Covers image collection, Docker setup, TFRecord conversion, and understanding GAN outputs for various projects like FishGAN and MinecraftGAN.
Cryptography Lab: Introduction to Hashing Techniques
Explore hashing techniques, salted passwords, and rainbow tables in cryptography through hands-on lab exercises and practical demonstrations.
Introduction to Cryptography Part 2 - Public Key and Key Exchange
Explore public key cryptography, hash functions, and key exchange methods. Learn about block vs. stream ciphers, salting, and one-way hashing for enhanced digital security.
Tokens, Authorization and Docker
Learn about authorization, tokens, and Docker in cybersecurity. Explore single sign-on, Active Directory, smart contracts, JSON Web Tokens, and FIDO for enhanced digital security and authentication.
Turning Caches into Distributed Systems with Mcrouter
Explore Facebook's mcrouter software for transforming standalone caches into robust distributed systems, addressing challenges like transient failures and multiple clusters.
Kyverno - Deep Dive - Tech Talks
Deep dive into Kyverno 1.9 features: mutation, generation, image verification, cleanup policies, and policy exceptions. Includes demos and best practices for secure software supply chain.