课程大纲
介绍
TensorFlow 概述
- 什么是 TensorFlow?
- TensorFlow 的功能
什么是人工智慧
- 计算心理学
- 计算哲学
Machine Learning
- 计算学习理论
- 计算经验的计算机演算法
Deep Learning
- 人工神经网路
- 深度学习 vs. 机器学习
准备开发环境
- 安装与配置 TensorFlow
TensorFlow 快速入门
- 使用节点
- 使用 Keras API
欺诈检测
- 读取和写入数据
- 准备特征
- 标记数据
- 正规化数据
- 将数据拆分为测试数据和训练数据
- 格式化输入图像
预测和回归
- 加载模型
- 可视化预测
- 创建回归
分类
- 建立和编译分类器模型
- 训练和测试模型
总结和结论
要求
- Python 编程经验
观众
- 数据科学家
客户评论 (5)
使用与我们在项目中使用的数据(光栅格式的卫星图像)更相似的数据进行更多实践练习的事实
Matthieu - CS Group
课程 - Scaling Data Analysis with Python and Dask
机器翻译
Very good preparation and expertise of a trainer, perfect communication in English. The course was practical (exercises + sharing examples of use cases)
Monika - Procter & Gamble Polska Sp. z o.o.
课程 - Developing APIs with Python and FastAPI
It was a though course as we had to cover a lot in a short time frame. Our trainer knew a lot about the subject and delivered the content to address our requirements. It was lots of content to learn but our trainer was helpful and encouraging. He answered all our questions with good detail and we feel that we learned a lot. Exercises were well prepared and tasks were tailored accordingly to our needs. I enjoyed this course
Bozena Stansfield - New College Durham
课程 - Build REST APIs with Python and Flask
Trainer develops training based on participant's pace
Farris Chua
课程 - Data Analysis in Python using Pandas and Numpy
I mostly enjoyed everything.