Published Feb 17, 2020

Real-time conversational insights from phone call data

Delve into the intricacies of AI-driven phone call analysis with Mike McCourt, as he shares his journey from astrophysics to data science at Invoca, exploring challenges in transcribing diverse dialects and enhancing marketing insights through unsupervised models that link calls to campaigns with precision.

Episode Highlights

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Episode Highlights

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Dexa/Practical AI

Real-time conversational insights from phone call data

Topics covered

Popular Clips

Unsupervised Language Methods

AI Career Transition

Physics to AI Transition

Unsupervised Method Development

Language Pattern Analysis

AI Transcription Challenges

Personalized AI Models

Automated Model Training

Phone Call Classification

Phone Number Optimization

Uncovering Language Patterns

Enhancing Marketing Insights

Phone Marketing Insights

Mirror Neurons Insight

Episode Highlights

AI Career Transitions

Conversational Data Challenges

Marketing Insights Enhancement

Unsupervised Method Development

Related Episodes

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The AI doc will see you now

On being humAIn

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Visualizing and understanding RNNs

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It's time to talk time series

Real-time conversational insights from phone call data

Topics covered

Popular Clips

Episode Highlights

AI Career TransitionsMike McCourt shares his transition from astrophysics to AI, highlighting how his background prepared him for a career in data science. He discusses his role at Invoca, where he leverages unique phone call data to drive AI innovations.

AI Career Transitions

Conversational Data ChallengesMike McCourt discusses the intricacies of transcribing phone calls and the challenges posed by diverse dialects and accents. He also explores how Invoca's classification models handle the variability in phone call data to ensure accurate analysis.

Conversational Data Challenges

Marketing Insights Enhancement

Unsupervised Method Development

Related Episodes