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机器学习入门
TensorFlow框架及常用库
机器学习实战
自然语言处理实战
图像识别实战
学习路线
学习前要求:Python编程基础(
Python学习路线),数学基础(线性代数、概率论、数理统计)。
学习后将掌握:机器学习和深度学习的概念,常用的机器学习算法和神经网络算法。
阶段 2:TensorFlow框架及常用库
4门课程 | 78课时
学习前要求:Python编程基础,了解常用的机器学习算法原理及实现,一定的英语读能力。
学习后将掌握:TensorFlow的基本使用,常用的Python科学计算库的使用。
学习前要求:了解常用机器学习算法、神经网络,了解TensorFlow框架及Python相关库的使用方法。
学习后将掌握:机器学习算法、神经网络的实战应用,阿里云机器学习PAI平台的操作。
阶段 4:自然语言处理实战
7门课程 | 67课时
学习前要求:了解神经网络,了解TensorFlow框架及Python相关库的使用方法。
学习后将掌握:机器学习/深度学习技术在自然语言处理(NLP)领域的实战应用。
学习前要求:了解神经网络,了解TensorFlow框架及Python相关库的使用方法。
学习后将掌握:机器学习/深度学习技术在图像识别处理领域的实战应用。