The Fundamentals of Gen AI and Machine Learning | Episode 1 | Learning Kerv

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In this episode, our host Rufus Grig, along with William Dorrington, CTO of Kerv’s digital transformation practice, Kerv Digital, Microsoft most valued professional, and a general all-round genius in the world of business technology, as our special guest.

Key highlights:

  • What is Artificial Intelligence (AI) and Machine Learning (ML)? Understand the basics of AI & ML and how machines can mimic human intelligence to perform tasks like decision-making and pattern recognition and why ML is essential to modern AI systems.
  • Applications of ML: Explore real-world examples of Machine Learning in action, from personalised recommendations to autonomous vehicles and healthcare solutions.
  • Difference between Model and Algorithm: Learn the distinction between algorithms (instructions for solving problems) and models (the outcome of training a model to make predictions).
  • Labelled vs Unlabelled Data: Find out how labelled and unlabelled data play a role in supervised and unsupervised learning, and why they’re critical to training AI models.
  • Training vs Inference: Understand the phases of training a machine learning model and how it uses what it learned to make predictions on new data during inference.
  • How AI Recognises Images/Text/Sound: Discover the technology behind AI’s ability to recognise images, transcribe speech, and process text.
  • Role of a Data Scientist: Gain insight into the role of a data scientist in building AI models, analysing data, and turning insights into actionable outcomes for businesses.

Join us as we explore the fundamentals of AI and discuss its transformative potential. Don’t miss out on this insightful conversation! If you want to talk to us further on this, please don’t hesitate to contact us: Contact Us for Inquiries, Support, and Business Collaboration | Kerv

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is now part of Kerv

In a continued effort to ensure we offer our customers the very best in knowledge and skills, Kerv has acquired Netwrx.