- 了解机器学习概念
- Python 程式设计经验
观众
- Business 分析师
- 数据科学家
- 开发人员
深度学习或深度结构化学习是机器学习的一个子集,涉及用于构建预测模型的多层网路。它广泛应用于医疗保健、电子商务、银行、制造、汽车等主要行业。
这种讲师指导的现场培训(在线或现场)面向希望构建和实施深度学习模型以加速收入增长和解决商业世界中问题的业务分析师、数据科学家和开发人员。
在本次培训结束时,参与者将能够:
- 了解机器学习和深度学习的核心概念。
- 通过 ML 和 DL 深入了解商业和行业的未来。
- 通过深度学习定义业务战略 和解决方案。
- 了解如何应用数据科学和深度学习来解决业务问题。
- 使用 Python、Pandas、TensorFlow、CNTK、Torch、Keras 等构建深度学习模型。
课程形式
- 互动讲座和讨论。
- 大量的练习和练习。
- 在即时实验室环境中动手实施。
课程自定义选项
- 要申请本课程的定制培训,请联系我们进行安排。
介绍
- Machine Learning (ML) 和 Deep Learning (DL) 概念概述
- ML 和 DL 的未来行业发展
Business 策略与 Deep Learning
- 定义业务问题
- 数据驱动的决策
- 分析思维和思维方式
- Business 策略建模
- 案例研究和示例
Deep Learning 软体和工具
- Python 和 Pandas 基本原理
- DL 开源工具(TensorFlow、CNTK、Torch、Keras 等)
- 使用案例和示例
Deep Learning 与 Neural Networks
- 神经网路学习 (反向传播)
- 卷积神经网路 (CNN)
- 递回神经网路 (RNN)
- DL 建模示例
总结和后续步骤
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