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An Introduction To Deep Learning & Computer Vision

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An Introduction To Deep Learning & Computer Vision

MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | Duration: 1.5 Hours | 433 MB
Genre: eLearning | Language: English
This course will get you started on two of the hottest topics in Machine Learning

Deep Learning is one of the hottest buzzwords out there in Machine Learning today - this class will get beyond the hype, and help you understand what it's all about! And along the way, you will write a Python program that recognizes handwritten digits!

Prerequisites: No prerequisites, knowledge of some undergraduate level mathematics would help but is not mandatory. Working knowledge of Python would be helpful if you want to run the source code that is provided.

Taught by a Stanford-educated, ex-Googler and an IIT, IIM - educated ex-Flipkart lead analyst. This team has decades of practical experience in quant trading, analytics and e-commerce.

Deep Learning Networks are the cutting edge solution for the handwritten digit recognition problem and many others in computer vision. These are often large artificial neural networks.
A quick introduction to Computer Vision, and one of the most popular starter problems - identifying handwritten digits using the MNIST database. We also talk about feature extraction from images.
Perceptron Reintroduced: The perceptron is the simplest of artificial neural networks - it becomes a building block for other complex networks
Python Activity: Simple Handwriting Recognition

Train a neural network to classify handwritten digits in Python. First start by downloading and unzipping the MNIST database images to create some training and test datasets.
Then we build a neural network and specify the training process.
We now have a trained neural network, feed it some test data and check the accuracy.
Mail us about anything, and we will always reply 🙂

An Introduction To Deep Learning & Computer Vision

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  1. 深度学习与计算机视觉导论 本教程将会带你开始学习机器学习领域两个最热门的主题。 深度学习是进来机器学习中流行的主题,本教程将会带你飞跃迷雾,真正了解其面目。然后你将会编写Python程序用以识别手写数字。 本教程无需任何现行知识准备,本课程度的数学即可,但也不是必须的。如果你打算运行源代码的话,那么懂得Python将会有所帮助。 讲授本教程的是前斯坦福、谷歌、IIT、IIM和Flipkart的员工组成的团队。他们具有几十年的实践经验在量化交易、分析和电子商务。 深度学习网络是手写数字识别问题和计算机视觉领域的最新解决方案。这些通常都是非常庞大的人工智能网络。教程将会使用MNIST数据库,从手写数字识别中最流行的一个初级问题开始学习。我们还会讲到图像中的提取功能。 Perceptron Reintroduced:最简单的人工智能认知问题,将会成为其他复杂网络的构建块。
    wilde(特殊组-翻译)1年前 (2016-03-11)