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AI & ML Engineering Summit

MLOps & AIOps

Managing artificial intelligence and machine learning projects often comes down to managing the enormous amounts of data and compute required to build functional models. In this track, we'll explore the technologies, processes, and best practices that make managing your AI/ML pipelines easier while improving your team's performance.


Tensorflow, PyTorch & Open Source Frameworks

Data is the lifeblood of modern organizations, but wading through that data to find patterns and make it actionable for the business remains a roadblock for many. In this track, we'll explore how AI/ML techniques are transforming data science and discuss the actions, processes, and technologies that can drive organizational insights to inform and inspire corporate growth and innovation.


Data Science & Predictive Models

Data science enables a company to utilize algorithms and predictive models to draw insights and forecasts from their data. What are the cutting-edge technologies and best practices for implementing data science initiatives in your company, and what types of predictive models prove the most useful?


Bots & Language Processing

Chatbots and natural language processing are rapidly redefining industries such as customer service and support, information search, knowledge management, and fraud detection. Learn how to utilize existing technologies to build your own chatbot or NLP solution.


Applied Machine Learning

This track targets both beginners and professionals looking to utilize open source or commercial machine learning technologies to implement business solutions. We will cover libraries and frameworks, training the AI with data, and analyzing / implementing results.


Deep AI Learning & Neural Networks

For AI professionals and advanced engineers, this track highlights the cutting edge of neural networks, automating human tasks through deep learning, advanced image / voice recognition, and thought leadership on the next phases of AI.