InfoQ Homepage QCon Software Development Conference Content on InfoQ
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Understanding ML/DL Models using Interactive Visualization Techniques
Chakri Cherukuri discusses how to use visualization techniques to better understand machine learning and deep learning models.
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Interpretable Machine Learning Products
Mike Lee Williams discusses how interpretability can make deep neural networks models easier to understand, and describes LIME, an OS tool that can be used to explore what ML classifiers are doing.
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Insecure Transit - Microservice Security
Sam Newman outlines some of the key challenges associated with microservice architectures with respect to security, and then looks at approaches to address these issues.
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Machine Intelligence at Google Scale
Guillaume LaForge presents pre-trained ML services such as Cloud Vision API and Speech API that works without any training, introducing Cloud AutoML.
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Fuelling the AI Revolution with Gaming
Alison Lowndes talks about the HW & SW that comprise NVIDIA's GPU computing platform for AI, across PC to data center, cloud to edge, training to inference.
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Tools to Put Deep Learning Models in Production
Sahil Dua discusses how Booking.com supports data scientists by making it easy to put their models in production, and how they optimize their model prediction infrastructure for latency or throughput.
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AI Panel
Panelists attempt to demystify AI and answer questions from the public.
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Disrupting the Banking Experience: Building a Mobile-Only Bank
Yann Del Rey and Teresa Ng provide some insight into how Starling Bank, a mobile-only bank, has built the mobile-banking apps and how they organize their teams to deliver new features, and more.
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Real-Time Data Analysis and ML for Fraud Prevention
Mikhail Kourjanski addresses the architectural approach towards the PayPal internally built real-time service platform, which delivers performance and quality of decisions.
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End-to-End ML without a Data Scientist
Holden Karau discusses how to train models, and how to serve them, including basic validation techniques, A/B tests, and the importance of keeping models up-to-date.
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Deep Learning for Science
Prabhat discusses machine learning's impact on climatology, astronomy, cosmology, neuroscience, genomics, and high-energy physics, and the future of AI in powering scientific discoveries.
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Liquidity Modeling in Real Estate Using Survival Analysis
Xinlu Huang and David Lundgren discuss hazard and survival modeling, metrics, and data censoring, describing how Opendoor uses these models to estimate holding times for homes and mitigate risk.
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