Detailed explanation of omnipotent Embedding 1 - Word2vec model & code implementation

Word2vec is a model proposed by Google in 2013, which trains word vectors from large-scale corpus. It is applied in many scenes, such as information extraction, similarity calculation and so on. Starting from word2vec, embedding has become popular in various fields, so word2vec is an appropriate opening. This paper hopes to give a more comprehe ...

Posted by Gordicron on Wed, 25 May 2022 17:17:02 +0300

libtorch study notes - MNIST combat

MNIST libtorch practical exercise Ready to work First download the MNIST database, http://yann.lecun.com/exdb/mnist/ After downloading, do not decompress it with software such as winrar. For example, t10k-images-idx3-ubyte is decompressed into t10k-images.idx3-ubyte. It is best to decompress it with tar in Linux environment. Suppose you unzip t ...

Posted by chrys on Wed, 25 May 2022 15:51:55 +0300

pytorch on GPU - training neural network with CUDA (pytorch series-30)

Running PyTorch code on GPU - neural network programming guide In this episode, we will learn how to use GPU and PyTorch. We will see how to use the general methods of GPU, and we will see how to apply these general techniques to train our neural networks. Deep learning using GPU If you haven't seen the episode about why deep learning and neur ...

Posted by bmbc on Mon, 23 May 2022 12:42:05 +0300

Regression Prediction of Vehicle Efficiency Using Fully Connected Neural Networks

Regression Prediction of Vehicle Efficiency Using Fully Connected Neural Networks keyword: fully connected neural network, tensorflow, regression illustrate It mainly uses the fully connected neural network to predict the regression problem of the car's performance index MPG. python packages include: os, pandas, tensorflow, sklearn, matplotlib ...

Posted by kevinc on Sun, 22 May 2022 19:00:03 +0300

TVM, acceleration model, optimization, inference

TVM is an open source deep learning compiler, which can be applied to all kinds of CPUs, GPUs and other special accelerators. Its goal is to enable us to optimize and run our own model on any hardware. Unlike the deep learning framework, which focuses on model productivity, TVM pays more attention to the performance and efficiency of the model ...

Posted by dkruythoff on Sun, 22 May 2022 09:15:51 +0300

Introduction to YOLO v3 algorithm

Picture from https://towardsdatascience.com/yolo-v3-object-detection-with-keras-461d2cfccef6 Data preprocessing Input picture dimension: (416, 416, 3) Input picture label: $[(x_1, y_1, x_2, y_2, class{\_}index), (x_1, y_1, x_2, y_2,class{\_}index), \ldots, (x_1, y_1, x_2, y_2,class{\_}index)] $represents all the real boxes marked in the pictur ...

Posted by messels on Fri, 20 May 2022 15:36:03 +0300

[Flying Paddle] Target Detection YOLO-V3 Study Notes

Before learning this course, I heard the name of YOLO. During the epidemic, an up master trained the detection of pedestrian masks through yolo and it was a great success. Without further ado, let's start learning. Basic Concepts in Object Detection Before starting to learn YOLO, first learn some basic concepts of target detection. After all, Y ...

Posted by Pro Ninja on Fri, 20 May 2022 08:48:32 +0300

SimpleRNN realizes stock forecast

Please check the previous articles for the principle. 1. Data source   SH600519.csv is the daily k-line data of sh600519 Guizhou Maotai downloaded by tushare module. In this example, only its C-column data is used (as shown in the figure):   use the opening price for 60 consecutive days to predict the opening price on ...

Posted by phpnewbie25 on Thu, 19 May 2022 23:01:07 +0300

[PyTorch] Note 02: Autograd auto derivation

From PyTorch 1.4 tutorial Outline Tensor torch.autograd.backward If the result node is scalar If the result node is a vector [PyTorch] Note 02: Autograd auto derivation In PyTorch, the core of all neural networks is autograd package 1 Tensor torch.Tensor is the core class of this autograd A Tensor tensor usually records the following ...

Posted by rusbb on Thu, 19 May 2022 21:17:09 +0300

Bayesian experiment report

1, Experimental purpose Learn how to infer the behavior model and solve the problem by using the short message mca-3. 2, Experiment contents and steps (including problems, codes, results and conclusions) 2.1 SMS data inference behavior Title: code: Data reading and display: import pymc3 as pm import matplotlib.pyplot as plt import nump ...

Posted by GYK on Mon, 16 May 2022 22:26:11 +0300