AI-NN-PR List Page 67

AI-NN-PR list

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mnist Downloaded：0: Using the fully connected network and convolution neural network, recurrent neural network builds different classifiers respectively, and how to save them through the preservation principle of the model.
Update : 2025-02-07 Size : 36.27mb Publisher : hhhwl
机器学习pics Downloaded：0: 17 thinking map +1 machine learning diagram
Update : 2025-02-07 Size : 3.45mb Publisher : 博闻工作室
基于bp神经网络的孤立词识别 Downloaded：0: bp matlab recongnation
Update : 2025-02-07 Size : 2.81mb Publisher : 璠璠李
Clustering-master Downloaded：0: A basic clustering algorithm, with data sets, is suitable for the preliminary study of clustering algorithm for human learning.
Update : 2025-02-07 Size : 21kb Publisher : siulietuiyiu
spr-7 Downloaded：0: Two thread random discrete convolution neural network is applied to feature extraction and classification for haptic sequences.
Update : 2025-02-07 Size : 4.02mb Publisher : scc不是二
Python网络数据采集 Downloaded：0: Python network data collection for those who want to learn how to use Python for network data acquisition.
Update : 2025-02-07 Size : 8.56mb Publisher : 林只只
LT-9 Downloaded：0: Two thread random discrete convolution neural network for LT-9 data set.
Update : 2025-02-07 Size : 6.05mb Publisher : scc不是二
生成对抗网络 Downloaded：0: Generate confrontation network for MNIST data set, implemented in Python language.
Update : 2025-02-07 Size : 3.37mb Publisher : scc不是二
matlab径向基函数网络 Downloaded：0: This is an example demonstrating the Radial Basis Function.
Update : 2025-02-07 Size : 8kb Publisher : 波澜壮阔-平淡如水
CNN_visual.py Downloaded：0: Image style transfer based on CNN
Update : 2025-02-07 Size : 582kb Publisher : ghostyhan
PC_ELM Downloaded：0: Autoencoder With Invertible Functions for Dimension Reduction andImage Reconstruction
Update : 2025-02-07 Size : 3kb Publisher : FrankXing
text_classification_AI100-master Downloaded：0: Achieve LSTM sentiment analysis, Chinese, use stuttering participle, LSTM model, environment python3.0
Update : 2025-02-07 Size : 4.66mb Publisher : 而近乎于

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