Neural Networks to Solve Multi-Classification Problems Example: Digit Recognition
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Neural Networks to Solve Multi-Classification Problems Example: Digit Recognition
1. Visualizing the data
2. Designing Nural Network
3. Write the cost function calculation function (nnCostFunction)
3.1 Implement the necessary tool functions
3.2 Normalized matrix definition
3.3 Implement forward propagation (Feedforward)
3.4 Implemen ...
Posted by jaoudestudios on Mon, 16 May 2022 01:00:12 +0300
NLP learning - text classification of NLP practice - Chinese spam classification - Python 3
1, Implementation steps of text classification:
Definition stage: define the data and classification system, which categories are divided and which data are needed Data preprocessing: prepare documents for word segmentation and de stop words Data extraction features: reduce the dimension of the document matrix and extract the most useful featu ...
Posted by lucerias on Mon, 16 May 2022 00:57:33 +0300
Linear regression prediction of Boston house prices
1, Experimental purpose
1. Understand the basic principle of linear regression and master the basic formula derivation.
2. Be able to manually implement fit and predict functions in LinearRegression by using formulas.
3. Be able to use the LinearRegression realized by yourself and the LinearRegression in sklearn to predict the house price in ...
Posted by murpe on Sun, 15 May 2022 22:10:37 +0300
Object search, detection and recognition using OpenCV
In this tutorial, we will understand the important concept called "selective search" in object detection. We will also share OpenCV code with C + + and Python.
Object detection and object recognition
The object recognition algorithm recognizes which objects exist in the image. It takes the whole image as the input and outputs the cl ...
Posted by master82 on Sun, 15 May 2022 11:40:45 +0300
[pytorch] code implementation of ECA-NET attention mechanism applied to ResNet
1, Foreword
Introduction to ECA-NET(CVPR 2020):
Thesis title:ECA-Net: Effificient Channel Attention for Deep Convolutional Neural NetworksThesis address:https://arxiv.org/abs/1910.03151Open source code:https://github.com/BangguWu/ECANet
As a lightweight attention mechanism, ECA net is actually an implementation form of channel attention mecha ...
Posted by phpflixnewbie on Sun, 15 May 2022 01:47:39 +0300
Principal Component Regression Analysis Practical Tutorial
This article introduces Principal Components Regression and demonstrates its implementation process through examples.
Given p predictors and response variables, multiple linear regression uses a method such as least squares to obtain the smallest sum of squared errors (RSS):
RSS =
Σ
...
Posted by quercus on Sun, 15 May 2022 00:24:16 +0300
Alink ramble: cluster evaluation of source code analysis
Alink ramble (22): cluster evaluation of source code analysis
0x00 summary
Alink is a new generation of machine learning algorithm platform developed by Alibaba based on Flink, a real-time computing engine. It is the first machine learning platform in the industry to support batch algorithm and streaming algorithm at the same time. This a ...
Posted by chenci on Sat, 14 May 2022 16:31:35 +0300
Preliminary study on ridge regression and LASSO regression (implemented in python)
As a rookie who has studied artificial neural network, I just heard about ridge regression estimation and LASSO estimation two days ago, and the statistics teacher also assigned homework. However, I didn't understand it very well and wrote it in Python. I don't know whether it is correct or not. Please do not hesitate to give advice where it is ...
Posted by LostKID on Sat, 14 May 2022 08:13:32 +0300
Machine learning notes 01_matplotlib drawing
Import required libraries
import matplotlib.pyplot as plt
import numpy as np
from jupyterthemes import jtplot
jtplot.style(grid=False)
Establish xy correspondence
x = np.linspace(-2, np.pi)
y1 = np.sin(x)
y2 = np.cos(x)
plot()
matplotlib. pyplot. Detailed explanation of plot () parameters https://matplotlib.org/api/pyplot_summary.html
# ...
Posted by thallium6 on Sat, 14 May 2022 06:49:55 +0300
Machine learning -- kMeans clustering
Related concepts
Unsupervised learning
Unsupervised learning is machine learning to learn the statistical law or internal structure of data from unlabeled data, mainly including clustering, dimension reduction and probability estimation. Unsupervised learning can be used for data analysis or pre-processing of supervised learning.
clustering ...
Posted by jamkelvl on Fri, 13 May 2022 02:19:17 +0300