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Introduction to Deep Learning

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Introduction to Deep Learning
Introduction to Deep Learning
MP4 | Video: AVC 1920x1080 | Audio: AAC 48KHz 2ch | Duration: 1 Hour | 999 MB
Genre: eLearning | Language: English

Deep learning neural networks have driven breakthrough results in computer vision, speech processing, machine translation, and reinforcement learning. As a result, neural networks have become an essential part of any data scientist’s toolkit. This video introduces neural networks created with Python and MXNet, a flexible and efficient deep learning library. The course explains what neural networks are, why they are powerful algorithms, and why they have a particular structure. It begins by introducing the core components of a neural network (i.e., nodes, weights, biases, activation functions, and layers) before showing you how to build a neural network in MXNet that solves a classic classification problem: identifying handwritten digits from grayscale images. Along the way, you'll learn about the backpropagation algorithm and how neural networks learn. Prerequisites include a basic understanding of Python, linear algebra, and calculus.

Learn what deep learning neural networks are, what they're used for, and why they're powerful
Discover the particular structure of neural networks and why it matters
Explore the basic concepts used in building and training neural networks
Understand how to build and train your own neural networks using MXNet
Develop a solid platform for learning more about deep learning and neural networks

Introduction to Deep Learning

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  1. 深度学习导论 深度学习神经网络已经在计算机视觉、语音识别、机器翻译以及增强学习领域取得了突破性的进展。这样的结果是神经网络已经成为任何一名数据科学家都必备的技能。本教程会介绍由Python和MXNet所开发的神经网络,一个灵活并且有效的深度学习类库。本教程会讲解何为神经网络,其算法为何强大以及他们的结构为何特别。在为你演示如何在MXMet中开发一个经典的从灰度图中识别手写数字的分类问题之前,教程会从介绍神经网络的核心概念开始。学习者应掌握基本的Python、线性集合和微积分的知识。 主要内容: • 学习何为深度学习神经网络,可以用其做什么以及为何它们是如此地强大 • 了解神经网络的特别结构以及为何重要 • 了解基本的用于开发和训练神经网络的概念 • 了解如何使用MXNet开发和培训你自己的神经网络 开发一个扎实的用于学习更多深度学习和神经网络的平台
    wilde(特殊组-翻译)2周前 (11-13)