Toronto Machine Learning Series (TMLS) Courses

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

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.

• YouTube
• 2 hours 15 minutes
• On-Demand
• Free Video

Holistic Health Metrics for ML-Based Products

Explore holistic health metrics for ML-based products. Learn where and when to collect data, model, post-model, and business-level metrics to ensure system accuracy and reliability.

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

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.

• YouTube
• 1 hour 26 minutes
• On-Demand
• Free Video

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.

• YouTube
• 1 hour 5 minutes
• On-Demand
• Free Video

Validate and Monitor Your AI and Machine Learning Models

Discover techniques for validating and monitoring advanced AI and ML models, ensuring long-term performance and business adoption in various industries.

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

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.

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

Introduction to Machine Learning with Python

Explore machine learning fundamentals using Python, covering key concepts and practical applications in this hands-on workshop led by a field engineer from Domino.

• YouTube
• 1 hour 55 minutes
• On-Demand
• Free Video

ML Monitoring ML: Scalable Monitoring of ML Models in Production Environments

Explore scalable ML model monitoring in production. Learn key performance measures, anomaly detection techniques, and an open-source agent for automated tracking and alerting of model issues.

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

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.

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

Reaching Lightspeed Data Science - ETL, ML, and Graph with NVIDIA RAPIDS

Accelerate data science workflows using GPUs and RAPIDS. Learn performance gains, easy migration, and new possibilities in ETL, ML, and graph analytics.

• YouTube
• 1 hour 19 minutes
• On-Demand
• Free Video

Modeling, Querying and Seeing Time Series Data within a Self-Organizing Mesh Network

Explore graph database modeling for dynamic power grid networks. Learn to query and analyze sensor data, triage at-risk components, and understand network healing processes.

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

Hyperparameter Tuning with a Focus on Weights and Biases Sweeps

Explore hyperparameter tuning strategies and visualizations for deep learning models, focusing on Weights & Biases Sweeps. Accelerate progress in semantic segmentation and language understanding projects.

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

MLOps at Scale: Predicting Bus Departure Times Using 18,000 ML Models

Explore MLOps at scale through a case study on predicting bus departure times using 18,000 ML models. Learn practical insights for implementing large-scale machine learning projects.

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