Google机器学习课程基于TensorFlow  : https://developers.google.cn/machine-learning/crash-course         https://developers.google.com/machine-learning/crash-course…
Lecture 10—Advice for applying machine learning 10.1 如何调试一个机器学习算法? 有多种方案: 1.获得更多训练数据:2.尝试更少特征:3.尝试更多特征:4.尝试添加多项式特征:5.减小 λ:6.增大 λ 为了避免一个方案一个方案的尝试,可以通过评估机器学习算法的性能,来进行调试. 机器学习诊断法 Machine learning diagnostic 的定义: 10.2 评估一个假设 想要评估一个算法是否过拟合 (一)首先,划分测试集和训练集…
引言: 最近开始学习"机器学习",早就听说祖国宝岛的李宏毅老师的大名,一直没有时间看他的系列课程.今天听了一课,感觉非常棒,通俗易懂,而又能够抓住重点,中间还能加上一些很有趣的例子加深学生的印象. 视频链接(bilibili):李宏毅机器学习(2017) 另外已经有有心的同学做了速记并更新在github上:李宏毅机器学习笔记(LeeML-Notes) 所以,接下来我的笔记只记录一些我自己的总结和听课当时的困惑,如果有能够帮我解答的朋友也请多多指教. 1.人工智能.机器学习.深度学习的关…
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Machine Learning Crash Course  |  Google Developers https://developers.google.com/machine-learning/crash-course/ Google's fast-paced, practical introduction to machine learning ML Concepts Introduction to Machine Learning As you'll discover, machine…
INDEX Introducing ML Framing Fundamental machine learning terminology Introducing ML What you learn here will allow you, as a software engineer, to do three things better. First, it gives you a tool to reduce the time you spend programming. Second, i…
INDEX How do we know if we have a good line Linear Regression Training and Loss How do we know if we have a good line So as we said before, our model is something that we learned from data.And there are lots of complicated model types and lots of int…
1.使用 TensorFlow 的建议 Which API(s) should you use? You should use the highest level of abstraction that solves the problem. The higher levels of abstraction are easier to use, but are also (by design) less flexible. We recommend you start with the high…
Goal of training a model is to find a set of weights and biases that have low loss, on average, across all examples. —— Descending into ML: Training and Loss 注释:教程中的 loss ≠ 平均方差,而是指单个 labeled example 的方差(也就是误差 loss ),这里的 reducing loss 是指减小整体的误差(就是 MS…
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