10X Faster Machine Learning: From R&D to Production
Offered By: Toronto Machine Learning Series (TMLS) via YouTube
Course Description
Overview
Discover how to accelerate machine learning processes from research and development to production in this comprehensive conference talk. Learn from three expert speakers as they share insights on overcoming challenges in complex ML model experimentation and productionization. Explore cutting-edge solutions proposed by the ML community to facilitate industry adoption of advanced models. Gain practical knowledge on supercharging your machine learning experimentation pipeline using tools like PyTorch Lightning and DVC. Understand how to streamline your path to production with Kubeflow and its add-ons. Benefit from the speakers' extensive experience in applied research, machine learning engineering, and building scalable ML pipelines. Dive into topics such as transfer learning, computer vision, state-of-the-art deep learning architectures, and large-scale solutions. Acquire valuable skills to make your ML processes up to 10 times faster and more efficient, from initial research to final deployment.
Syllabus
10X Faster Machine Learning From R&D to Production
Taught by
Toronto Machine Learning Series (TMLS)
Related Courses
End to End Deep Learning Project Using MLOPS DVC Pipeline With Deployments Azure and AWS - Krish NaikKrish Naik via YouTube Open Source Tools for ML Experiments Management
Linux Foundation via YouTube Automating Machine Learning Workflow with DVC
EuroPython Conference via YouTube Transforming a Jupyter Notebook into a Reproducible Pipeline for ML Experiments
PyCon US via YouTube End-to-End Deep Learning Project: Kidney Disease Classification with MLflow, DVC, and Deployment
Krish Naik via YouTube