How to Get Your Website Into the Cloud
Deploy your GitHub portfolio to cloud hosting using Infrastructure as Code. Learn Terraform, avoid pitfalls, and follow best practices in this interactive workshop on cloud deployment.
AI on the Edge - Advancing Edge Computing and Next-Generation Networks
Explore AI's role in advancing edge computing and next-gen networks. Discover opportunities for AI on the edge in DOD Microelectronics Commons Program.
Functional Tokens for On-device Multimodal Models - Nexa AI
Explore innovative functional tokens for on-device multimodal AI models, enhancing accuracy and efficiency in function calling tasks while achieving remarkable performance across languages and modalities.
Fine-Tuning Language Models with Declarative ML Orchestration
Gain hands-on experience using Flyte to declaratively specify infrastructure for fine-tuning language models on your own data, overcoming compute resource challenges.
Leveraging ML Recommendation Models to Improve Customer Engagement
Explore personalization in retail using Amazon Personalize. Learn about ML-powered recommendation systems, real-time personalized experiences, and their impact on customer engagement.
Responsible AI Toolbox: Practical Approaches and Tools for Ethical Machine Learning
Explore practical approaches to responsible AI and learn how open-source and cloud-integrated capabilities empower data scientists to understand and improve ML models ethically.
Deep AutoViML for TensorFlow Models and MLOps Workflows
Explore Deep AutoViML for building powerful TensorFlow models and MLOps workflows. Learn to fast prototype data pipelines and models using TF 2.4+ and Keras preprocessing layers.
MCUNet: TinyML on Microcontrollers - Lecture 10
Explore MCUNet for TinyML on microcontrollers, covering efficient neural architecture design and deployment strategies for resource-constrained devices.
On-Device Training and Transfer Learning - Lecture 19
Explore on-device training and transfer learning techniques for efficient machine learning, focusing on practical applications and cutting-edge methodologies.
On-Device Training and Transfer Learning - Lecture 19
Explore on-device training and transfer learning techniques for efficient machine learning, focusing on practical applications and cutting-edge methodologies.
EfficientML.ai: Introduction to Efficient Machine Learning - Lecture 1
Explore efficient machine learning techniques and their applications in this introductory lecture from MIT's EfficientML course.
EfficientML.ai: Introduction to Efficient Machine Learning - Lecture 1
Explore efficient machine learning techniques and their applications in this comprehensive introduction to EfficientML.ai from MIT's Prof. Song Han.
Microservices: Go Native and Containerize with Java and Quarkus
Explore native and containerized microservices using Java and Quarkus. Learn to build efficient, scalable applications with cutting-edge technologies.
BigQuery: Google's Cloud Data Warehouse - Lecture 24
Explore Google BigQuery's architecture, query processing, and optimization techniques with insights from a leading database systems expert.
Amazon Redshift Internals - Lecture 24
Explore Amazon Redshift's architecture, design principles, and performance optimizations with insights from a guest lecturer and former CMU PhD graduate.
OtterTune: AI-Powered Database Optimization as a Service
Explore AI-powered database optimization with OtterTune, revolutionizing performance tuning through machine learning and automation.
Akamas: Autonomous Performance Optimization
Explore autonomous performance optimization techniques for complex IT systems using AI-driven approaches and continuous experimentation methodologies.
Distributed Data Warehouse OLAP Databases - Lecture 23
Explore distributed data warehouse OLAP databases, covering architecture, query processing, and optimization techniques for large-scale analytical systems.
Realtime Data Streaming - End-to-End Data Engineering Project
Build a real-time data streaming pipeline using Apache Airflow, Kafka, Spark, and Cassandra. Learn end-to-end data engineering, from ingestion to processing and storage, all containerized with Docker.
Google Cloud Real-Time Streaming - End-to-End Data Engineering Project
Build an end-to-end data engineering pipeline for real-time YouTube Analytics, using Python, Google Cloud, Docker, and Kafka. Learn to fetch, process, and stream data, with instant Telegram notifications.
Football Data Analytics: Azure End-to-End Data Engineering Project
Extract, clean, and analyze football data using Apache Airflow, Azure services, and Tableau. Build a comprehensive data pipeline from Wikipedia to interactive visualizations.