In everyday data processing for Machine Learning and Data Science projects, we encounter unique situations, those require boilerplate code to solve the problem. Over the period some of those are converted into base features provided by the core langu…
a = np.arange(2*4*4) b = a.reshape(1,4,4,2) #应该这样按反序来理解:最后一个2是一个只有2个元素的向量,最后的4,2代表4×2的矩阵,最后的4×4×2代表立体张量,第一个1代表只有一个这样的张量(即该张量在第四维度只有一个元素). c = a.reshape(2,4,4,1) #应该这样按反序来理解:最后一个1是只有一个1个元素的向量,最后的4,1代表4×1的矩阵(可降维成一个向量),最后的4×4×1代表立体张量(可降…
numpy 简介 numpy的存在使得python拥有强大的矩阵计算能力,不亚于matlab. 官方文档(https://docs.scipy.org/doc/numpy-dev/user/quickstart.html) Quickstart tutorial Prerequisites Before reading this tutorial you should know a bit of Python. If you would like to refresh your memory,…
Quickstart tutorial 引用https://docs.scipy.org/doc/numpy-dev/user/quickstart.html Prerequisites Before reading this tutorial you should know a bit of Python. If you would like to refresh your memory, take a look at the Python tutorial. If you wish to w…
Python Basics with numpy (optional)Welcome to your first (Optional) programming exercise of the deep learning specialization. In this assignment you will: - Learn how to use numpy. - Implement some basic core deep learning functions such as the softm…
Welcome to your first assignment. This exercise gives you a brief introduction to Python. Even if you've used Python before, this will help familiarize you with functions we'll need. Instructions: You will be using Python 3. Avoid using for-loops and…
Python Basics with Numpy (optional assignment) Welcome to your first assignment. This exercise gives you a brief introduction to Python. Even if you've used Python before, this will help familiarize you with functions we'll need. Instructions: You wi…