What we’re about
MLTO: Machine Learning Toronto is a community for data and AI professionals in the Greater Toronto Area. Our mission is to create a group of like-minded individuals to build networks authentically, learn from industry experts, and share knowledge in free and open events focused on genuine connection, learning, and discussion around developments in AI. We believe that by bringing together individuals from diverse backgrounds, we can create a space that promotes learning and growth in the field for the benefit of all involved.
Follow us on LinkedIn: www.linkedin.com/company/mlto-machine-learning-toronto/
Upcoming events (2)
See all- Machine Learning TO (MLTO) Monthly MeetupOneEleven, Toronto, ON
Agenda
6:00-6:30 PM Arrivals and Networking
6:30-7:00 PM Tech Talk #1
7:00-7:30 PM Tech Talk #2
7:30-8:30 PM Networking & Wrap-up
8:30 PM Tear-down and DeparturesTech Talks
Talk #1 - Three levels of Agent building - Deterministic, Workflows and Agentic - Denys Linkov, Head of ML @ VoiceflowUsing the right tools for the right job is an essential component of building products and software engineering. In this talk, we'll cover how to approach agent building along a spectrum of Agentic behaviour. We'll focus on tradeoffs in terms of latency, cost, time to build, accuracy and more.
Talk #2 - Creating Agents in Google Vertex AI: An LLM and GPT Introduction - Devang Sharma, Software Development Engineer @ Amazon
The talk will provide an overview of Generative AI. It will begin by defining the field and explaining how generative AI models function. As an introduction to the field, we will specifically look at the GPT series of models, and explore real-world applications of generative AI. Finally, we will dive hands-on into Vertex AI and Gen AI Studio on Google Cloud, demonstrating an example of using them in development of an agent-based generative AI solution.
About the Speakers
Denys Linkov is the Head of Machine Learning at Voiceflow, ML Advisor and Linkedin Learning Course Instructor. He's worked with 50+ enterprises in their conversational AI journey, and his Gen AI courses have helped 150,000+ learners build key skills. He's worked across the AI product stack, being hands on building key ML systems, managing product delivery teams, and working directly with customers on best practices.Devang Sharma is a Senior Full Stack Developer with 7+ Years of hands-on experience in Analysis, Development, and Implementation with solid Programming expertise in - Java, Golang, Node.js, C#, Perl, Javascript, Typescript, ReactJs, Angular, PHP, C/C++, Python, Microservices and Distributed Services along with System Design and Object-Oriented Methodologies with a demonstrated history of working in the Internet Industry.
Speak or Support MLTO!
We are constantly looking for new speakers and sponsors to share their knowledge and help build the AI community in the GTA! If you are interested please get in touch directly or apply via one of the links below:- Speaker Application Form: mlto.ca/speak
- Sponsor Inquiry Form: mlto.ca/sponsor
- Volunteer Application Form: mlto.ca/volunteer
- Machine Learning TO (MLTO) Monthly MeetupOneEleven, Toronto, ON
Agenda
6:00-6:30 PM Arrivals and Networking
6:30-7:00 PM Tech Talk #1
7:00-7:30 PM Tech Talk #2
7:30-8:30 PM Networking & Wrap-up
8:30 PM Tear-down and DeparturesTech Talks
Talk #1 - Building A Cost-Effective Machine Learning Platform: Scaling Enterprises with Open Source Magic - Emin Mammadov, GeotabTalk #2 - Graph RAG: Beyond the hype, with practical implementations - Prashanth Rao, Kuzu
In this talk, we will cover the basics of graphs, graph databases, and their role in building Graph RAG systems. We will also cover the evolution of RAG (Retrieval-Augmented Generation) and how graphs can play a role. The audience will walk away having learned some history and also some practical implementations that they can then try out on their own data, using open source tools and frameworks.About the Speakers
Emin Mammadov is a Senior Software Developer, specializing in building scalable machine learning platforms at Geotab. After graduating from University of Waterloo, he worked as a data scientist, data engineer, and machine learning engineer in several industries. Passionate about data and software engineering, solving complex problems and finding practical and cost effective solutions for real world problems. In his free time, you can find Emin in a local coffee shop reading or snowboarding in Blue Mountains.Prashanth Rao is an AI engineer at Kùzu Inc., an embedded graph database startup in Ontario, Canada. He has two master's degrees: in Aerospace engineering from the University of Michigan, and in Computer Science from Simon Fraser University. In recent years, he’s worked on a variety of data engineering, data science and machine learning problems and has thought deeply about databases and data modeling paradigms. In his spare time, Prashanth enjoys hiking, biking, trying out new cuisines, engaging with the AI developer community, and blogging about all things data @ thedataquarry.com.
Speak or Support MLTO!
We are constantly looking for new speakers and sponsors to share their knowledge and help build the AI community in the GTA! If you are interested please get in touch directly or apply via one of the links below:- Speaker Application Form: mlto.ca/speak
- Sponsor Inquiry Form: mlto.ca/sponsor
- Volunteer Application Form: mlto.ca/volunteer
