Wednesday, March 13, 2019
Flatten, Reshape, and Squeeze Explained - Tensors for Deep Learning with...
Matrix is a rank 2 tensor. There are two axis one is an array, one is individual numbers.
Check the dimensions of tensors using .size() or .shape()
Obtain the rank of the tensor by checking the length of its shape
len(tensor.shape) #returns 2 for matrix
number of elements in the tensor, is the product of the component values in the shape torch.tensor(my_tensor.shape).prod()
my_tensor.numel() #number of elements
number of elements is important in reshaping
reshaping does not change underlining data just change the shape
Uniqtech guide to Machine Learning. This guide explains the difference between machine learning, traditional programming, machine learning w...
Can hack schools solve Silicon Valley's talent crunch? The truth about coding bootcamps and the students left behind http://t.co/xXNfqN...
The bogus request from P2PU to hunt for HTML tags in real life has yielded a lot of good thoughts. My first impression was that this is stup...
This review is updated continuously throughout the program. Yay I just joined the Udacity Nanodegree for Digital Marketing! I am such an Uda...