使用 Python 和 TFlearn 深度学习的第一步

《使用 Python 和 TFlearn 深度学习的第一步》

近年来，深度学习已经带动了机器学习的革命性进展：用于分类图像和自动翻译的深层神经网络模型已经达到了过去无法想象的程度。

我们将快速概述深度神经网络和激活函数，然后使用 TFlearn 构建图像分类器。 TFlearn 使用类似 sklearn 的接口，一个流行的 Python 机器学习库，利用谷歌的 TensorFlow 的底层计算和加快开发过程。 听课只需具备一些 Python 知识即可，无需机器学习背景。

《First steps in deep learning with Python and TFlearn》

In recent years deep learning has caused a revolution in machine learning: using so-called deep neural networks models for classifying images and automatic translation with before unimaginable quality have been build.

We will give a quick overview about deep neural nets and activition functions and then proceed to build an image classifier using TFlearn. TFlearn uses an interface similar to sklearn, a popular Python machine learning library. It leverages Google's TensorFlow for the underlying computation and speeds up the development process. Only minimal Python skills and no prior experience with machine learning are necessary.