• Five simple steps to master tensorflow tensor


    Author | Orhan g. YAL ç ı nCompile VKSource: towards Data Science If you are reading this article, I believe we have similar interests and will engage in similar industries now / in the future. In this article, we will delve into the details of tensorflow tensor. We will cover all topics related to tensorflow’s […]

  • Application and exploration of Python artificial intelligence in Snake game


    So how do we deal with the data reasonably? We know that the state in Q (s, a) represents the state of the snake. This state includes the position of the apple, the position of the snake, the position of the boundary, the distance between the snake and the boundary, and so on. How to […]

  • Implementation of TPU CNN model by pytorch


    By Dr. Vaibhav KumarCompile VKSource: analytics in diamag With the successful implementation of deep learning model in various applications, it is time to obtain not only accurate but also faster results. In order to get more accurate results, the size of data is very important, but when this size affects the training time of machine […]

  • Pytorch realizes the conversion of tensor, image, CPU, GPU, array and so on


    1. Create the tensor of Python torch.rand ((322424)) # create a random value of 3D tensor with the size of (322424) torch.Tensor ([3,2]) create tensor, [3,2] 2. The conversion between the tensors on CPU and GPU, that is, the tensors created by python b = a.cpu() # GPU → CPU a = b.cuda() #CPU → […]

  • Pytorch to delete the specified row and column in the tenor


    preface In Python, if you want to delete the specified row and column in the tendon, you thought you could have a function or assign a line to [] directly. It turns out that it’s not so simple. So you use a curve to save the country. I hope you can point out a more […]

  • Tensorflow learning – 1


    Tensorflow learning – 1   If life is just like seeing for the first time, what’s the matter with autumn wind.   Introduction:Tensorflow basic use, constant / variable, tensorflow 2.0 compatible with tensorflow 1.0. 1、 Code examples 1 import tensorflow as tf 2 3 print(“tensorFlow version is: ” + tf.__version__) 4 5 # create two […]

  • The most complete pytorch data scientist’s Guide (1)


    All the pytorch features you’ll need for deep learning. From an experimental / research point of view. PyTorchIt has become one of the de facto standards for creating neural networks, and I like its interface. However, it is difficult for beginners to get it. I remember choosing pytorch a few years ago after extensive experiments. […]

  • Tensorflow2.0-mnist handwritten numeral recognition example


    Tensorflow2.0-mnist handwritten numeral recognition example       When you read, you don’t realize that spring is deep, and every inch of time is golden.   Introduction:After training by CNN convolution neural network, handwritten images are recognized, and 0, 1, 2, 4 in MNIST dataset are tested.                     […]

  • The open source JavaScript Library of pandas Danfo.js Now available!


    Author: rising odegua and Stephen oni | source: tensorflow Danfo.js JavaScript is an open source library, which provides high-performance, intuitive and easy-to-use data structure, and supports the operation and processing of structured data. Danfo.js Inspired by the python pandas library, it provides a similar interface / API. Therefore, users who are familiar with pandas API […]

  • [pytorch learning notes] 1.2 introduction to tensor


    thumbnail: https://image.zhangxiann.com/…toc: truedate: 2020/2/5 20:39:20disqusId: zhangxiancategories: PyTorch tags: AI Deep Learning Code of this chapter: https://github.com/zhangxiann/PyTorch_Practice/blob/master/lesson1/tensor_introduce1.py https://github.com/zhangxiann/PyTorch_Practice/blob/master/lesson1/tensor_introduce1.py The concept of tensor Tensor is tensor in Chinese. Tensor means a multidimensional array, which is a high-dimensional extension of scalar, vector and matrix. Scalar can be called 0-dimensional tensor, vector can be called 1-dimensional tensor, matrix can […]

  • Simple use of Python tensor flow


    This paper describes the simple use of Python tensor flow. For your reference, the details are as follows: 1. Basic concepts Tensor stands for tensor, which is a data structure of multidimensional array. Flow stands for flow, which refers to the process of conversion between tensors through calculation. Tensorflow represents the programming process in the […]

  • Building efficient custom datasets in pytorch


    Learn the context of the dataset class, use a clean code structure, and minimize the hassle of managing large amounts of data during training. Neural network training may be difficult to achieve “large scale” in data management. Pytorch has been in my circle recently, and although I’m happy with keras and tensorflow, I still have […]