Gain exclusive digital access to talks and slides from all past DataScienceSalon events

Talks

Topics

Companies

ABOUT DATA SCIENCE SALON

Data Science Salons are one or two-day events hosted at Blue Chip companies that focus on AI and machine learning applications in media, entertainment, retail, ecommerce, finance, healthcare and technology industries. These intimate events curate data science sessions to bring specialists in these verticals face-to-face to educate each other on innovative new solutions in artificial intelligence, machine learning, predictive analytics and acceptance around best practices. Data Science Salon attendees are executives, senior data science practitioners, data science managers, analysts, and engineering professionals. The format includes a combination of talks, workshops, and panels.

SPEAKERS FROM TOP Companies

Get access to the best ideas and business uses cases from the top data decisionmakers at blue chip companies.

And many more!!

Impactful Data Science Insights

Discover and explore recordings from past DSS technical talks, panels, and business use cases, covering all major topics in machine learning, AI, and data science.

Exclusive content portal

Experience the full power of the Data Science Salon with access to recorded talks, slides, abstracts, and speaker contact info.

 

Featured Speakers

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Topics include

• Putting ML apps into production
• Personalization at scale with AI
• Cloud automation and machine learning
• Natural language processing & deep learning
• Engineering for data science
• Scaling ML production
• Improving data quality
• Machine learning best practices
• Data strategy and governance
• Data ethics and bias
• Recommendation engines

• Designing ML pipelines efficiently
• Deep neural networks
• Image recognition with ML
• Using large scale data sets
• Data science teams: managing, building, collaboration
• Integrating open source tools into your workflows
• Enhancing the viewer experience with machine learning & AI
• Content personalization and monetization
• Audience targeting and segmentation (across platforms)
• Data and AI for emerging platforms
• Data governance