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About Mastering Deep Learning Fundamentals With Python
This document provides an overview of deep learning fundamentals and their history. It discusses how early approaches like artificial neural networks were limited by their inability to utilize more than a few hidden layers. Modern deep learning techniques emerged by applying ideas from random matrix theory to deep neural networks, allowing them to scale to many layers and achieve major successes in areas like computer vision and natural language processing. The document also outlines key concepts in probability, statistics, and machine learning that helped lay the foundations for deep learning.
Detailed Information
| Author: | ['Quebec Immigration Doc'] |
|---|---|
| Publication Year: | 2024 |
| Pages: | 172 |
| Language: | English |
| Format: | |
| Price: | FREE |
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