AI & ML Real-World Project Success Stories
What was your entire AI & ML project lifecycle, and what did you learn along the way, in order to launch a successful project? Learn from top tech companies about their AI & ML success stories.
AI & ML-as-a-Service
Instead of deploying your own custom artificial intelligence or machine learning solution, we are seeing a new era of accessing artificial intelligence, machine learning, and data science solutions “as a service” via API or a developer interface. In an age when more of the technology stack is becoming decentralized, serverless, and on-demand, AI & ML-as-a-service makes intensive machine learning operations accessible to any developer.
Training Data, Models, and Feasibility
Before you can kick off your machine learning project, you first need to ask yourself: Is the model or algorithm suitable – and do you have enough training data for the model? Talks in this track discuss successes and failures of finding suitable models and training data.
TensorFlow is one of the most popular open-source machine learning technologies, and you can get up to speed on the latest developments and best practices of this technology. Pioneered by the Google Brain team, TensorFlow makes large-scale machine learning projects faster and easier.
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.
Developing Artificial Intelligence Technologies
Are you a software engineer, data scientist, or architect who is developing their own artificial intelligence solution? This track spotlights the success stories and best practices from innovative engineers.
Bots & Language Processing
Chatbots and natural language processing is 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.
AI for the Enterprise
What are the most common use cases for an enterprise to utilize AI? From ad targeting and customer intelligence to data analytics and security, this track will highlight success stories of using AI in the enterprise.
Deep AI and 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.
The emerging AI track covers the newest AI technologies for software engineers, data scientists, CTOs, and business users.
AI Open Source
What are the newest open source AI tools, libraries, and technologies? Hear their technology pitches and meet the most disruptive open source technologies in the market.