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AI vs. Machine Learning vs. Deep Learning vs. Neural Networks: What’s the difference?

IBM Big Data Hub

While artificial intelligence (AI), machine learning (ML), deep learning and neural networks are related technologies, the terms are often used interchangeably, which frequently leads to confusion about their differences. How do artificial intelligence, machine learning, deep learning and neural networks relate to each other?

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Conversational AI: Design & Build a Contextual Assistant – Part 1

CDW Research Hub

Recent advances in machine learning, and more specifically its subset, deep learning, have made it possible for computers to better understand natural language. These deep learning models can analyze large volumes of text and provide things like text summarization, language translation, context modeling, and sentiment analysis.

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Breaking down the advantages and disadvantages of artificial intelligence

IBM Big Data Hub

AI development and deployment can come with data privacy concerns, job displacements and cybersecurity risks, not to mention the massive technical undertaking of ensuring AI systems behave as intended. For optimal performance, AI models should receive data from a diverse datasets (e.g.,

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Themes and Conferences per Pacoid, Episode 7

Domino Data Lab

Seriously, this entire article merely skims the surface of those reports. Check the end of this article for key guidance synthesized from the practices of the leaders in the field. Evolving Data Infrastructure: Tools and Best Practices for Advanced Analytics and AI (Jan 2019). One-fifth use reinforcement learning.