课程描述
Deep Learning with Python and Keras is a tutorial from the Udemy site that introduces you to deep learning and teaches you how to create different models for images and text using the Python language and the Keras library. This course is designed for beginners and intermediate level programmers and those familiar with Python and helps them to learn deep learning techniques and apply them to various problems.
Deep Learning with Python and Keras 是 Udemy 网站上的一个教程，向您介绍深度学习，并教您如何使用 Python 语言和 Keras 库为图像和文本创建不同的模型。本课程专为初学者和中级程序员以及熟悉 Python 的人设计，帮助他们学习深度学习技术并将其应用于各种问题。
At the beginning of the course, you will be introduced to the basics of this science by learning a Deep Learning app, and you will also learn about machine learning tools and techniques. Then you learn artificial neural networks and learn how to use them in solving regression and classification problems. The tutor goes on to introduce various architectures such as recursive neural networks, torsional neural networks, and fully connected networks, explaining various theoretical and practical examples. At the end of the course you will be able to identify problems by deep learning and design different neural network models.
在课程开始时，您将通过学习深度学习应用程序了解这门科学的基础知识，您还将学习机器学习工具和技术。然后你学习人工神经网络并学习如何使用它们来解决回归和分类问题。导师接着介绍了递归神经网络、扭转神经网络和全连接网络等各种体系结构，并解释了各种理论和实践示例。在课程结束时，您将能够通过深度学习识别问题并设计不同的神经网络模型。
Courses taught in this course:; 本课程讲授的课程：
- Understanding deep learning
- 了解深度学习
- Using deep learning to build predictable models
- 使用深度学习构建可预测模型
- Use deep learning in different applications
- 在不同的应用程序中使用深度学习
- Using Python and Keras to build deep learning models
- 使用 Python 和 Keras 构建深度学习模型
- Solve various problems with the help of deep learning
- 借助深度学习解决各种问题
- Practicing and running models in the cloud using GPUs
- 使用 GPU 在云端练习和运行模型
- Estimation of training costs for large models
- 大型模型训练成本的估算
Deep Learning with Python and Keras course specifications:; 使用 Python 和 Keras 进行深度学习课程规范：
- English language
- 英语
- Duration: 9 hours 56 minutes
- 持续时间：9 小时 56 分钟
- Number of lessons: 148
- 课时数：148
- Level of education: Intermediate
- 教育程度：中级
- Instructor: Data Weekends, Jose Portilla, Francesco Mosconi
- 讲师：Data Weekends、Jose Portilla、Francesco Mosconi
- File format: mp4
- 文件格式：mp4
Course headings; 课程标题
148 lectures 09:56:50
148 讲 09:56:50
Welcome to the course!
8 lectures 37:12
欢迎来到课程！ 8 节课 37:12
Date
18 lectures 01:04:58
日期 18 讲座 01:04:58
Machine Learning
22 lectures 02:04:11
机器学习 22 讲 02:04:11
Deep Learning Intro
17 lectures 01:16:39
深度学习简介 17 个讲座 01:16:39
Gradient Descent
26 lectures 01:45:14
梯度下降 26 讲 01:45:14
Convolutional Neural Networks
23 lectures 01:20:33
卷积神经网络 23 讲座 01:20:33
Cloud GPUs
2 lectures 1:14
云 GPU 2 个讲座 1:14
Recurrent Neural Networks
13 lectures 45:13
循环神经网络 13 个讲座 45:13
Improving performance
19 lectures 01:01:41
提高绩效 19 讲 01:01:41
课程描述
- Knowledge of Python, familiarity with flow control (if / else, for loops) and pythonic constructs (functions, classes, iterables, generators)
- Python 知识，熟悉流程控制（if / else，for 循环）和 pythonic 结构（函数、类、可迭代对象、生成器）
- Use of bash shell (or equivalent command prompt) and basic commands to copy and move files
- 使用 bash shell（或等效的命令提示符）和基本命令来复制和移动文件
- Basic knowledge of linear algebra (what is a vector, what is a matrix, how to calculate dot product)
- 线性代数基础知识（什么是向量，什么是矩阵，如何计算点积）
- Use of ssh to connect to a cloud computer
- 使用ssh连接云电脑
课程描述
Sample movie; 样片
课程描述
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Subtitle: Has
副标题：有
Quality: 720p
画质：720p
课程描述
