Optimizing Neural Networks for Efficient Data Processing





Published 3/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 48 KHz
Language: English | Size: 173.48 MB | Duration: 34m 34s

Learn to optimize neural networks for efficiency and performance. This course will teach you how to reduce model size and improve performance using the right techniques.


The efficiency and performance of neural networks are important for fast, lightweight, and energy-efficient AI solutions.
In this course, Optimizing Neural Networks for Efficient Data Processing, you'll gain the ability to optimize neural networks to achieve better performance with less computational resources and energy consumption.
First, you'll explore the fundamentals of neural network efficiency, covering topics like weight initialization and optimization algorithms to start your models in the right way.
Next, you'll discover regularization techniques to improve model generalization and prevent overfitting, ensuring your models are robust and reliable.
Finally, you'll learn how to apply model pruning and quantization techniques to significantly reduce model size and improve speed, making your models ideal for deployment.
When you're finished with this course, you'll have the skills and knowledge of neural networks optimization needed to create efficient and high-performing AI models.

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