Machine Learning Models Courses and Certifications

USENIX

Stealing Machine Learning Models via Prediction APIs

Explores model extraction attacks on machine learning systems, demonstrating vulnerabilities in publicly accessible ML interfaces and proposing potential countermeasures to protect confidential models.

• YouTube
• 28 minutes
• On-Demand
• Conference Talk

Data Science Dojo

Building Robust Machine Learning Models from Noisy Labeled Data - Improving ML Model

Learn strategies for building robust ML models using noisy labeled data, addressing subjective responses, and tracking distribution bias through model monitoring. Enhance your ML systems with practical insights.

• YouTube
• 58 minutes
• On-Demand
• Free Video

Data Science Dojo

Hands-on Introduction to Interpreting Machine Learning Models

Explore methods for interpreting machine learning models, including feature importance and local explanations, to increase trust in AI products and bridge gaps in problem understanding.

• YouTube
• 1 hour 7 minutes
• On-Demand
• Free Video

Data Science Dojo

Deploying Machine Learning Models with Flask and Docker

Learn to deploy ML models as web services using Flask, manage environments with Pipenv, package with Docker, and deploy to AWS Beanstalk. Gain practical skills for putting models into production.

• YouTube
• 1 hour 13 minutes
• On-Demand
• Free Video

Data Science Dojo

Building Robust Machine Learning Models

Explore the fundamentals of robust machine learning, focusing on data quality, feature engineering, and model evaluation rather than specific tools or trendy techniques.

• YouTube
• 1 hour 25 minutes
• On-Demand
• Free Video

Databricks

Tuning Machine Learning Models - Scaling, Workflows, and Architecture

Automating and scaling ML model tuning using Hyperopt and Apache Spark. Best practices for workflows, architecture, and optimization in hyperparameter tuning for improved performance and accuracy.

• YouTube
• 24 minutes
• On-Demand
• Free Video

Institute for Advanced Study

Stop Explaining Black Box Machine Learning Models for High Stakes Decisions and Use Interpretable Models Instead - Cynthia Rudin

Advocating for interpretable machine learning models in high-stakes decisions, highlighting their reliability and transparency compared to black box models with potentially misleading explanations.

• YouTube
• 1 hour 4 minutes
• On-Demand
• Free Video

Serving Machine Learning Models at Scale Using KServe

Explore KServe's Multi-Model Serving solution for scalable machine learning deployment, addressing resource limitations and enabling efficient GPU utilization in Kubernetes clusters.

• YouTube
• 31 minutes
• On-Demand
• Conference Talk

EuroPython Conference

Explaining Behavior of Machine Learning Models with ELI5 Library

Explore techniques for interpreting and debugging ML models using eli5 library. Learn to explain linear models, decision trees, ensembles, and classifiers, improving trust and quality in ML solutions.

• YouTube
• 30 minutes
• On-Demand
• Conference Talk

PyCon US

Testing Machine Learning Models

Explore techniques for testing ML/AI models beyond metrics, focusing on behaviors, usability, and fairness. Learn to identify risks, biases, and apply user-centric testing strategies.

• YouTube
• 31 minutes
• On-Demand
• Conference Talk

Inside Livermore Lab

Generalizing Scientific Machine Learning and Differentiable Simulation Beyond Continuous Models

Explore generalizing scientific machine learning beyond continuous models, covering differentiable simulation for chaotic systems, stochastic processes, and inverse problems in advanced scientific computing.

• YouTube
• 58 minutes
• On-Demand
• Free Video

MIT HAN Lab

Diffusion Models in Efficient Machine Learning - Lecture 16

Explore diffusion models in-depth, covering theory, applications, and efficient implementation techniques for advanced machine learning practitioners.

• YouTube
• 1 hour 16 minutes
• On-Demand
• Free Video

MIT HAN Lab

Diffusion Models in Machine Learning - Lecture 16

Explore diffusion models in machine learning, covering theory, applications, and efficient implementation techniques for advanced AI image generation.

• YouTube
• 1 hour 16 minutes
• On-Demand
• Free Video

Wolfram

What's Really Going On in Machine Learning? Some Minimal Models - Stephen Wolfram Reading

Explore Stephen Wolfram's insights on machine learning through minimal models, covering neural nets, discrete rule arrays, and optimization processes. Gain a deeper understanding of ML fundamentals and their implications.

• YouTube
• 2 hours 23 minutes
• On-Demand
• Free Video

Yannic Kilcher

Machine Learning News: Chips, Robots, and Models - April 2024 Update

Comprehensive update on AI advancements: new chips, models, and industry developments. Covers breakthroughs in language models, vision-language models, and AI applications across tech giants and startups.

• YouTube
• 39 minutes
• On-Demand
• Free Video