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import numpy as np import pandas as pd import tensorflow as tf from tensorflow import feature_column from tensorflow.keras import layers from sklearn.model_selection import train_test_split data URL = 'https://storage.googleapis.com/applied-dl/heart.csv' dataframe = pd.read_csv(URL) train, test = train_test_split(dataframe, test_size=0.2) ...

Introduction: logistic regression is a very common means of classification. It belongs to probabilistic nonlinear regression, which is divided into two classification and multi classification regression models. For binary logistic regression, the dependent variable y has only two values of "yes" and "no", which are recorded ...

sigmoid activation function Function expression: Function image: From this figure, we can see the following characteristics of sigmoid activation function: 1. When the input is greater than zero, the output must be greater than 0.5 2. When the input exceeds 6, the output will be infinitely close to 1, and the discrimination function of ...

During the development of some application projects, voice detection functions are sometimes needed, that is, the functions of recognizing knocking, door ringing, car horn sound and so on. For small and medium-sized developers, developing and building this ability alone is time-consuming and labor-consuming. However, the voice recognition servi ...

1. Background In the recommendation system, the common targets are ctr and cvr. The data of these two targets are tilted seriously. If the sample is not sampled, the model is easy to learn bias, resulting in unstable online effect and poor generalization ability. 2. Sample sampling and processing 2.1 sample purification Usually, the pulled ...

brief introduction This paper will introduce how to use OpenBox open source black box optimization system to optimize the super parameters of LightGBM model. OpenBox is an open source system designed for black box optimization (project address: https://github.com/thomas-young-2013/open-box ), based on Bayesian optimization, the black bo ...

We often encounter all kinds of errors in writing strategies, which is very cumbersome, but it is an essential step in procedural trading. In fact, there are only a few reasons and types of errors in JoinQuant operation. python code format error, such as indentation and unequal usage - this can be basically solved by Baidu or google error pro ...

12. Image smoothing 12.1 objectives Learn: - blur images with various low-pass filters - apply custom filters to images (2D convolution) 12.2 # 2D convolution (image filtering) Like the one-dimensional signal, various low-pass filters (LPF) and high pass filters (HPF) can also be used to filter the image. LPF helps to eliminate noise and blu ...

Data set partition Firstly, the data set is divided into training set, verification set and test set, marked as X,y, Xval,yval and Xtest,ytest. The content of data set division can be seen This blog. Data visualization The first step of Wu Enda's routine operation is data visualization. Here, only the training set is visualized: % Load ...

I Machine learning overview Watch the introduction video of dark horse programmer's machine learning at station B and write this note to consolidate knowledge. Video link of station B Relevant information can be found in the comment area of the video. 1.1 definition: Machine learning is to automatically analyze and obtain the model from the ...