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所在平台: Udemy |
课程主页: https://www.udemy.com/course/keras-deep-learning-in-python/
课程评论：没有评论
课程名称：Keras：Python中的深度学习 课程概述： 您想要在Keras中构建复杂的深度学习模型吗？您希望使用神经网络进行图像分类、价格预测和多类别样本分类吗？Keras是Python中构建神经网络模型最强大的库。在本课程中，我们将回顾Keras中的核心技术，并通过许多现实生活中的实例进行说明。我们专注于实际的计算实现，避免使用复杂的数学公式。 参加本课程的学生需具备Python和机器学习的基础知识；一些统计和概率的常识是推荐的，但并非严格要求。课程中我们将通过多个示例进行学习，比如使用神经网络标记属于泰晤士河或街道的图像；分类可食用和有毒的蘑菇；预测多个区域的电子游戏销售；识别图像中的螺栓和螺母等。虽然大部分示例是在Windows上进行，但我们也会展示如何在AWS机器上设置和运行这些示例。 在课程大纲方面，我们覆盖了Keras的主要功能，如Sequential模型、模型API、卷积神经网络（CNN）、长短期记忆网络（LSTM）等。我们还展示了如何绕过Keras，直接使用Theano/Tensorflow语法构建模型（尽管这相对复杂！） 完成本课程后，您应该能够自信地构建适用于时间序列、图像分类、无监督分类和回归的神经网络。所有讲座内容均可下载，并附有相应的材料。
Do you want to build complex deep learning models in Keras? Do you want to use neural networks for classifying images, predicting prices, and classifying samples in several categories?Keras is the most powerful library for building neural networks models in Python. In this course we review the central techniques in Keras, with many real life examples. We focus on the practical computational implementations, and we avoid using any math.The student is required to be familiar with Python, and machine learning; Some general knowledge on statistics and probability is recommended, but not strictly necessary.Among the many examples presented here, we use neural networks to tag images belonging to the River Thames, or the street; to classify edible and poisonous mushrooms, to predict the sales of several video games for multiple regions, to identify bolts and nuts in images, etc.We use most of our examples on Windows, but we show how to set up an AWS machine, and run our examples there. In terms of the course curriculum, we cover most of what Keras can actually do: such as the Sequential model, the model API, Convolutional neural nets, LSTM nets, etc. We also show how to actually bypass Keras, and build the models directly in Theano/Tensorflow syntax (although this is quite complex!)After taking this course, you should feel comfortable building neural nets for time sequences, images classification, pure classification and/or regression. All the lectures here can be downloaded and come with the corresponding material.
