End-to-End MLOps for Computer Vision
Explore end-to-end MLOps for Computer Vision, from data gathering to model monitoring. Learn to implement ML pipelines using tools like Amazon SageMaker, Kubernetes, Kubeflow, and MLFlow.
Implementing MLOps Practices on AWS using Amazon SageMaker
Implement ML pipelines with CI/CD practices using SageMaker Pipelines. Gain hands-on experience in MLOps, incorporating DevOps principles into machine learning workflows for scalable and efficient model deployment.
Image Processing with AWS - AWS Machine Learning and Artificial Intelligence
Comprehensive overview of AWS image processing, machine learning, and AI services, featuring hands-on demos of SageMaker, Rekognition, Comprehend, Polly, and Textract for practical applications.
Amazon SageMaker
Learn to build, train, and deploy ML models using AWS SageMaker, covering notebook instances, S3 buckets, XGBoost algorithm, and endpoint predictions.
Amazon SageMaker Technical Deep Dive Series
Comprehensive deep dive into Amazon SageMaker, covering notebook instances, algorithms, custom models, training, deployment, tuning, and advanced features for efficient machine learning workflows.
Amazon SageMaker Tutorial - How to Use Amazon SageMaker for Machine Learning
Learn to build, train, and deploy machine learning models using Amazon SageMaker. Explore its architecture, features, and hands-on implementation for streamlined ML development and production.
Improving Productivity for Building ML Workloads Using Amazon SageMaker Autopilot
Automate ML model training and tuning for customer churn prediction using Amazon SageMaker Autopilot, with deployment and iteration in SageMaker Studio.
Build, Train, and Deploy Models with Amazon SageMaker
Learn to build, train, and deploy machine learning models using Amazon SageMaker through hands-on experience. Gain practical skills in ML model development and implementation on AWS platform.
Serverless for Machine Learning Pipelines
Explore serverless architecture for ML/DL deployment, utilizing AWS services to organize scalable and affordable deep learning workflows for efficient model training and operationalization.
Managed Training with Amazon SageMaker and Transformers
Explore SageMaker and Hugging Face integration for efficient NLP model training, deployment, and optimization. Learn preprocessing, hyperparameter tuning, and model compression techniques.
Deep Learning for Price Action Prediction Using Databricks and AWS
Explore deep learning techniques to enhance price action prediction using Databricks and AWS. Learn to optimize technical indicators and train models with Amazon SageMaker for improved financial forecasting.
Generative AI and Large Language Models: Fine-tuning with SageMaker, PEFT, RLHF and PPO
Master advanced LLM fine-tuning techniques using Amazon SageMaker, exploring PEFT, RLHF, and PPO methodologies for optimized AI model performance and customization.
Responsible AI in Industry - Lessons Learned in Practice
Explore practical lessons on implementing responsible AI in industry, covering explainability, fairness, and challenges faced by major tech companies.
The Psychology of UX
Explore the psychology behind UX design, cognitive biases, and digital decision-making. Learn to influence choices through environmental interventions and develop digital consciousness skills.
Serverless & Event-Driven Patterns for GenAI
Explore serverless and event-driven patterns for GenAI, learning efficient architectures for hosting, training, and consuming AI solutions on AWS at scale. Gain insights into EDA options for various business use cases.
Innovating at Speed - AWS and Formula 1
Explore how AWS and Formula 1 leverage data analytics and machine learning to enhance race performance, make predictions, and provide fans with deeper insights into the high-speed world of motorsports.
Building Scalable End-to-End Deep Learning Pipelines in the Cloud
Explore serverless deep learning on AWS using Batch, Fargate, SageMaker, Lambda, and Step Functions to create scalable, cost-effective pipelines for efficient model development and deployment.
Getting Started with GenAI for Android Apps
Explore GenAI integration in Android apps, covering basic concepts, major AI solutions, and practical mobile use cases. Learn to leverage AI capabilities effectively.
MLflow - Platform for Complete Machine Learning Lifecycle
Discover how MLflow simplifies machine learning development by tracking experiments, registering projects, and streamlining model deployment across various platforms.
Mastering Generative AI: Harnessing AWS GenAI for Your Solutions
Explore AWS GenAI solutions, from foundation models to Amazon Bedrock and Claude 3. Learn about customization, knowledge bases, agents, and CodeWhisperer for innovative AI implementation.
Train Your First NLP Transformer Model with Amazon SageMaker
Learn to train and deploy NLP Transformer models using Amazon SageMaker and Hugging Face. Gain hands-on experience with cutting-edge deep learning techniques for natural language processing.