@ArtOfTheProblem
  @ArtOfTheProblem
Art of the Problem | Why Deep Neural Networks Beat Shallow Ones. #ai #technology #science @ArtOfTheProblem | Uploaded 9 months ago | Updated 9 hours ago
FULL VIDEO: youtube.com/watch?v=e5xKayCBOeU Why do neural networks need to be deep? In this video we explore how neural networks transform perceptions into concepts. This video unravels the mystery behind how machines interpret input data, such as images or sounds, and categorize them into recognizable concepts. From the basic structure of neurons and layers to the intricate play of weights and activations, get a comprehensive understanding of the learning process. Explore real-world applications like handwriting recognition and how layered processing aids in effective data categorization. Whether it's distinguishing between summer and winter days based on temperature and humidity or recognizing handwritten digits, the magic lies in the layered architecture of neural networks. This video elucidates how these artificial networks mimic the human brain's ability to interpret, recognize, and reason, marking a significant stride in AI research towards creating machines capable of reasoning. Why layers matter.
Why Deep Neural Networks Beat Shallow Ones.  #ai #technology #scienceSneak PeekAncient Information Theory (Semaphores & signal fires)What is a bit? (Information Theory)Fermats Little Theorem (Visualization)Public key cryptography - Diffie-Hellman Key Exchange (full version)Deep Learning Worked.Bitcoin Documentary | The Trust MachineConditional probability (Bayes Theorem) explained visuallyCan you detect a coin flip? #quiz #gambling #statisticsDiscrete Logarithm ProblemClaude Shannons Perfect Secrecy

Why Deep Neural Networks Beat Shallow Ones. #ai #technology #science @ArtOfTheProblem

SHARE TO X SHARE TO REDDIT SHARE TO FACEBOOK WALLPAPER