Dataset Cartography: What Capital One Monitors to Better Manage AI Training Data
Explore dataset cartography techniques used by Capital One to enhance AI training data management and improve model performance.
Towards Digital Twins for Precision Medicine
Explore digital twins in precision medicine, covering virtual trials, theranostics, AI, data management, and future prospects in personalized healthcare.
Knowledge Graph Recommendation Systems for COVID-19
Explore knowledge graph recommendation systems for COVID-19, leveraging Python skills to enhance understanding of pandemic-related data and insights.
Computer Vision in Practice - Building an End-to-End Pipeline for Object Detection and Segmentation
Build an end-to-end image segmentation pipeline using deep learning. Learn dataset customization, model training, validation, testing, and mobile deployment techniques.
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.
Women in AI - Transitioning Careers, Challenges, and Opportunities
Explore career transitions, challenges, and opportunities for women in AI through insights from industry experts and leaders.
Simplify ML Pipeline Automation and Tracking Using Kubeflow and Serverless Functions
Simplify ML pipeline automation and tracking with Kubeflow and serverless functions. Learn to streamline your machine learning workflows for improved efficiency and productivity.
Automated Pipeline for Large-Scale Neural Network Training and Inference
Explore cloud-native ML pipeline for automated anomaly detection using BiLSTM models. Learn to manage thousands of models with data collection, training, validation, and deployment techniques.
MLOps and Automation Workshop - Bringing Machine Learning to Production in a Few Easy Steps
Learn to deploy ML/AI to production faster using MLOps technologies. Explore automation techniques and best practices for efficient machine learning operations.
Building an AI Capability in the United States Army
Explore the development of AI capabilities in the U.S. Army with insights from Chief Data Scientist LTC Isaac J Faber PhD.
Algorithmic Decision Making - Exploring Practical Approaches to Liability, Fairness, and Explainability
Explore practical approaches to liability, fairness, and explainability in algorithmic decision-making with industry experts.
Banorte's AI Journey - Yielding 3 Billion USD Revenue in 5 Years
Explore Banorte's AI transformation journey, yielding $3 billion in revenue over 5 years. Learn strategies for implementing high-ROI AI projects and avoiding transformational fatigue.
Accelerating Talent in AI - Overcoming Industry Challenges
Explore key obstacles in AI talent acquisition and strategies to overcome them, empowering academia, graduates, and businesses to bridge the industry-ready talent gap.
Enhancing Machine Learning Applications with Wisdom of the Crowd
Explore ensemble techniques to boost ML model performance, explainability, and usability for complex problems by leveraging multiple specialized models.
Machine Learning in Finance - Lessons Learned
Explore ML's impact on finance, its current capabilities, and best practices for implementation. Learn to identify opportunities and avoid pitfalls in trading and banking applications.
Simplifying Machine Learning Lifecycle Management in Healthcare
Explore end-to-end ML lifecycle in healthcare using Azure services. Learn data ingestion, model creation, deployment, and visualization for real-time patient predictions and batch scoring.
Simplifying Machine Learning Lifecycle Management in Healthcare
Simplify ML lifecycle management in healthcare with practical insights and strategies for efficient model development, deployment, and monitoring.
Enabling a Data-Driven Enterprise - Part 1
Discover strategies for building a data-driven organization, reducing AI bias, and fostering human-machine collaboration to drive innovation in enterprise settings.
How to Set Your Internal AI Initiative for Production-Level Success
Explore strategies for maximizing AI project success in production, building credibility with decision-makers, and selecting high-impact initiatives within organizations.
Machine Learning in One Health
Explore machine learning applications in One Health, addressing interconnected human, animal, and environmental health issues with Graham Taylor, a leading AI researcher and entrepreneur.
Deep Learning Across Label Confidence Distribution via Transfer Learning
Improve predictive power in noisy data systems using Filtered Transfer Learning (FTL). Learn to handle datasets with varying label confidence through hierarchical fine-tuning and iterative filtering.