Toronto Machine Learning Series (TMLS) Courses

Why ML in Production is Still Broken

Explore challenges in deploying ML projects to production, focusing on the disconnect between development and real-world application. Learn key aspects distinguishing ML from traditional software engineering.

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

How to Monitor Machine Learning Stacks - Detecting and Addressing Special Issues

Discover advanced monitoring techniques for ML stacks, addressing unique challenges beyond traditional metrics to ensure robust performance and early issue detection.

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

Deep Learning for Program Repair

Explore Google's ML4SE research on training deep learning models to fix software build errors, enhancing developer productivity and reducing project delays.

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

Docker Based Workflow for Deploying a Machine Learning Model

Explore Docker's role in ML development, from container basics to full deployment, focusing on reproducibility, portability, and ease of implementation.

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

Machine Learning with PyCaret - Workshop

Explore rapid prototyping and ML pipeline development using PyCaret, an open-source, low-code machine learning library for Python.

• YouTube
• 1 hour 2 minutes
• On-Demand
• Free Video

Industry Survey Analysis: The Industry Landscape of Natural Language Use Cases in 2020

Explore industry survey results on natural language systems in production, examining recent advances, practical use cases, and adoption trends across technology subcategories in NLP.

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

AI Value for Investors and Key Factors Attracting Investment in AI Companies

Explore AI investment strategies, evaluate AI pitches, and discover key factors attracting investors to AI companies. Gain insights from industry experts on assessing AI value and potential.

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

A Tale of A Thousand Pipelines: Building Scalable Deep Learning Pipelines for Time-Series Datasets

Discover scalable deep learning pipelines for massive time-series datasets, reducing costs by 80% while training hundreds of models efficiently.

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

Team Roles in a Machine Learning Project and Project Flow

Develop context for data science projects, understand team roles, and build a data-driven culture. Learn about machine learning techniques and their appropriate applications.

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

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.

• YouTube
• 1 hour 2 minutes
• On-Demand
• Free Video

Productionizing ML Models for Online Shopping at Loblaws

Explore ML model productionization for online shopping, covering microservices, CI pipelines, AB testing, and cloud-based implementation using tools like Seldon Core.

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

How to Automate Machine Learning with GitHub Actions

Automate machine learning workflows using GitHub Actions to speed up development cycles and streamline model deployment.

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

Managing Data Science in the Enterprise

Learn effective strategies for managing data science teams, processes, and technologies in enterprise settings, avoiding pitfalls and implementing best practices for breakthrough results.

• YouTube
• 1 hour 41 minutes
• On-Demand
• Free Video

Deploying Deep Learning Models to the Edge

Discover techniques for deploying Tensorflow models to mini-robots, enabling edge AI applications in compact devices.

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

Turbo-Charging Data Science with AutoML

Explore open-source AutoML tools and cloud provider options to enhance data science workflows. Hands-on demonstration of installation, usage, and unique features for improved efficiency.

• YouTube
• 1 hour 49 minutes
• On-Demand
• Free Video