Why Quadratic Cost Functions Are Ineffective in Neural Network Training

Machine Learning Tech Brief By HackerNoon

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18 روز پیش36:44

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36:44

In this episode of the Innovators and Investors Podcast, host Kristian Marquez sits down with Amar Bakshi, founder of Shared Studios and Noro, to explore how Amar’s visionary work is redefining human connection through immersive technology. Amar shares the evolution from his original art project, which connected strangers worldwide via life-size video portals installed in locations from New York to Tehran, refugee camps, and universities, to creating Noro’s cutting-edge video conferencing solutions that bridge the gap between virtual meetings and face-to-face interaction. They discuss the inspiration behind his projects, including his personal experiences as a journalist and his grandmother’s story of displacement, highlighting the emotional and cultural impact of authentic human connection. Amar explains the challenges of building a global network in complex political environments, the importance of community-led curation, and leveraging technology to enable deeper trust and collaboration beyond traditional video calls like Zoom. The conversation also covers insights into building company culture, navigating the transition from art to business, raising capital, and how AI and future tech innovations could enhance multilingual communication and intimacy in virtual settings. Amar closes by sharing lessons learned as a founder about balancing commitment with perspective and fostering inclusive, purpose-driven teams. This episode provides a thoughtful look at how technology can create meaningful, serendipitous human connections across borders and industries. Learn more about Amar's work at https://noro.co/ Connect with Amar on LinkedIn at https://www.linkedin.com/in/amarcbakshi/ Think you'd be a great guest on the show? Apply at https://finstratmgmt.com/innovators-investors-podcast/podcast-guest-application/ Want to learn more about Kristian Marquez's work? Check out his website at https://finstratmgmt.com…

حدود یک سال پیش 8:12

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This story was originally published on HackerNoon at: https://hackernoon.com/why-quadratic-cost-functions-are-ineffective-in-neural-network-training.
Explore why quadratic cost functions hinder neural network training and how cross-entropy improves learning efficiency in deep learning models.
Check more stories related to machine-learning at: https://hackernoon.com/c/machine-learning. You can also check exclusive content about #deep-learning, #neural-networks, #what-is-cross-entropy, #sigmoid-activation-function, #neural-network-training, #quadratic-cost-function, #cross-entropy-cost-function, #hackernoon-top-story, and more.
This story was written by: @varunnakra1. Learn more about this writer by checking @varunnakra1's about page, and for more stories, please visit hackernoon.com.
One of the most common question asked during deep learning knowledge interviews is - “Why can’t we use a quadratic cost function to train a Neural Network?**” We will delve deep into the answer for that. There will be a lot of Math involved but nothing crazy! and I will keep things simple yet precise.

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Why Quadratic Cost Functions Are Ineffective in Neural Network Training

Machine Learning Tech Brief By HackerNoon

published حدود یک سال پیش

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316 قسمت

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