雖然這篇Binarized MNIST鄉民發文沒有被收入到精華區：在Binarized MNIST這個話題中，我們另外找到其它相關的精選爆讚文章
[爆卦]Binarized MNIST是什麼？優點缺點精華區懶人包
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#1binarized_mnist | TensorFlow Datasets
A specific binarization of the MNIST images originally used in (Salakhutdinov & Murray, 2008). This dataset is frequently used to evaluate generative models of ...
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#2Binarized MNIST Dataset | Papers With Code
A binarized version of MNIST. ... Binarized MNIST. A binarized version of MNIST. Source: Binarized MNIST. Homepage. Benchmarks. Edit.
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#3Binarized MNIST in VAE tutorial · Issue #529 - GitHub
The model in the VAE tutorial has a Bernoulli observation model. However, the images from MNIST (after preprocessing) have values in [0, 1], ...
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#4Comparison between data from binarized MNIST and random ...
Download scientific diagram | Comparison between data from binarized MNIST and random samples generated from the three models by randomly initializing ...
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#5Difference between grayscaled and binary mnist dataset
Why is the mnist dataset grayscaled and not binarized? Will it have any postive or negative effects when applying the binarized images in a ...
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#6Binarize MNIST - Google Groups
Is there a quick way to binarize the MNIST dataset that comes with Torch? ... Is something like a threshold function?
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#76 MNIST Image Datasets That Data Scientists Should Be ...
... QKMNIST, EMNIST, binarized MNIST and 3D MNIST. ... MNIST(Modified National Institute of Standards and Technology) database contains ...
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#8Binary MNIST in literature : Machine Learning - Reddit
2015年4月27日 — I'd like to find resources about a binarized version of MNIST, i. e. one with image pixels being only black or white not gray scaled.
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#9Ben Poole on Twitter: "PSA: if you're benchmarking a ...
How would a(nother) randomly binarized MNIST have significantly more optimistic performance than Hugo's MNIST? I can see how deterministically that is the ...
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#10MNIST with binary color | madflex
To evaluate this I changed the dataloader in the PyTorch MNIST example to ... The first lambda binarizes the values in every tensor and the ...
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#11Datasets — MLPython 0.1 documentation - Université de ...
Dataset store; 20-newsgroups; Abalone; Adult; Bibtex; Binarized MNIST; Cadata; CIFAR-10 ... datasets.binarized_mnist: binarized version of MNIST module.
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#12Binarized Neural Networks - NeurIPS Proceedings
Last but not least, we wrote a binary matrix multiplication GPU kernel with which it is possible to run our MNIST BNN 7 times faster than with an unoptimized ...
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#13Downloaders — Fuel 0.2.0 documentation
The binarized MNIST dataset files ( binarized_mnist_{train,valid,test}.amat ) are downloaded from Hugo Larochelle's website [HUGO].
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#14Bit Error Tolerance of a CIFAR-10 Binarized Convolutional ...
Finally, we compare the measured error rates for the CIFAR-10 binarized ConvNet against MNIST networks to demonstrate the difference in bit error ...
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#15Binary Classification of MNIST with pytorch
do you think normalizing would make sense if I binarize the MNIST set? thanks in advance! Home · Categories · FAQ/Guidelines ...
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#16Binarized Neural Network (BNN) and Its Implementation in ...
... BNN on MNIST 7 times faster, achieving near state-of-the-art results. In this article, we'll see how Binarized Neural Networks work.
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#17Training Deep Neural Networks with Weights and Activations ...
Title:Binarized Neural Networks: Training Deep Neural Networks ... to run our MNIST BNN 7 times faster than with an unoptimized GPU kernel, ...
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#18Masked Autoencoder for Distribution Estimation on Small ...
We compare the proposed methods with some related binary, discrete, and continuous density estimators on MNIST, binarized MNIST, OCR-letters, ...
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#19Synaptic metaplasticity in binarized neural networks - Nature
a Problem setting: two training sets (here MNIST and Fashion-MNIST) are presented sequentially to a fully connected neural network. When ...
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#20Binarized Neural Network Application on Zynq MPSoC ZU9 ...
Input images: 28x28 pixels, binarized MNIST. – 3 Fully Connected layers, 256 neurons each. – Neural network implementation: 19.5kLUTs (7% of device), ...
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#21Discriminative learning for discrete MNIST data using ...
This notebook shows how to build a randomly structured SPN and train it to classify digits using a TensorFlow optimizer on binarized MNIST data.
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#22Performance Comparison of Binarized Neural Network with ...
The research demonstrates the adding of dropout layer to a BNN for MNIST and. CIFAR10 datasets, and shows that it might provide improvement to the baseline ...
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#23BinaryGAN | Training GANs with Binary Neurons by ...
The proposed model is able to directly generate binary-valued predictions at test time. We implement such a model to generate binarized MNIST digits and ...
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#24Digit Recognizer - Amazon AWS
The MNIST database of handwritten digits, has a training set of 60,000 examples ... images the raw data, and in the second set of pizels the binarized data.
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#25Neuromorphic Binarized Polariton Networks | Nano Letters
We demonstrate that binarized neurons can operate in a fully all-optical ... linear classification for the full and binarized MNIST input.
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#261 Binarized Neural Networks (BNNs) - SINTEF
FINN: A Framework for Fast, Scalable Binarized Neural ... image classification rates at <25 W power and <1 ms latency for MNIST and CIFAR-10 datasets.
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#27Introduction to BNNs with Larq
This tutorial demonstrates how to train a simple binarized Convolutional Neural Network (CNN) to classify MNIST digits. This simple network will achieve ...
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#28Variational Inference with Normalizing Flows on MNIST
Finally, we can train a generative model with the objective defined above on the Binarized MNIST dataset. Here are some sample from this ...
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#29shark::MNIST Class Reference
Reads in the famous MNIST data in possibly binarized form. The MNIST database itself is not included in Shark, this class just helps loading it.
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#30practical lossless compression with latent variables using bits ...
Figure 1: Visual comparison of 30 binarized MNIST images with bitstream outputs from running lossless compression algorithms PNG, bz2 and BB-ANS on the ...
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#31Table 4 | A Reweighted Scheme to Improve the ... - Hindawi
Binarized -MNIST, 0.0301, 0.0265, 0.0312. Connect-4, 0.26783, 0.25443, 0.28364. Convex, 0.29632, 0.28502, 0.30658. DNA, 0.16948, 0.15346, 0.15936.
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#32Digital Biologically Plausible Implementation of Binarized ...
In parallel, the recently proposed concept of a Binarized Neural Network ... Based on neural networks on multiple datasets (MNIST, CIFAR-10, ...
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#33Single-pixel sensing with optimal binarized modulation
The effectiveness of SPS is experimentally demonstrated on the classification task of the handwritten MNIST dataset, and 96% classification accuracy at ...
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#34Binarized Neural Networks with Replicated Secret Sharing
Experimen- tally, we implement BaNNeRS on top of MP-SPDZ and compare it with prior work over binarized models trained for MNIST and CI-. FAR10 image ...
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#35Bidirectional Helmholtz Machines - Department of Statistical ...
Figure 2. Inpainting of binarized MNIST digits. The left column in each block shows the original digit randomly sampled from the. MNIST test set; the first ...
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#36Neural Autoregressive Flows - NASA/ADS
... NAF yields state-of-the-art performance on a suite of density estimation tasks and outperforms IAF in variational autoencoders trained on binarized MNIST.
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#37[PDF] Verifying Properties of Binarized Deep Neural Networks
Figures, Tables, and Topics from this paper · Deep learning · Verification and validation · Scalability · MNIST database · Computer vision · Boolean algebra · Neural ...
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#38On better training the infinite restricted Boltzmann machines
Experiments on binarized MNIST and CalTech101 Silhouettes have shown that, RP can train the hidden units more efficiently, thus results in ...
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#39Memristor crossbar array for binarized neural networks - AIP ...
The feasibly working binarized neural network adopting the electroforming-free ... such as MNIST (Modified National Institute of Standards and Technology).
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#40A Review of Binarized Neural Networks - MDPI
Abstract: In this work, we review Binarized Neural Networks (BNNs). ... Instead of processing the MNIST dataset with convolutions they used.
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#41Binarized neural networks - ACM Digital Library
Last but not least, we wrote a binary matrix multiplication GPU kernel with which it is possible to run our MNIST BNN 7 times faster than with ...
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#42Implementing Binarized Neural Networks with ...
examples of image recognition tasks (MNIST, CIFAR-10 and. ImageNet): bit error rates of ST-MRAM up to 0.1% have.
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#43Neuromorphic Binarized Polariton Networks
Recently, binarized neural networks, in which the activations or ... (MNIST) data set, using a simple single-hidden-layer network.
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#44MADE: Masked Autoencoder for Distribution Estimation - PURE
layer, 500 hidden units network, on binarized MNIST. taken from the literature. Again, despite its tractability,. MADE is competitive with other models.
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#45Sparsity-Inducing Binarized Neural Networks - Association for ...
this work, we propose the Sparsity-inducing Binarized Neu- ral Network (Si-BNN), ... datasets, such as MNIST and CIFAR-10 (Courbariaux and. Bengio 2016).
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#46An Infinite Restricted Boltzmann Machine | Neural Computation
We compare the performance of the oRBM and the iRBM with the classic RBM on two data sets: binarized MNIST (Salakhutdinov & Murray, ...
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#47Embedded Binarized Neural Networks - Brad McDanel
ple, eBNN achieves 95% accuracy on the MNIST dataset running on an Intel Curie with only 15 KB of usable mem- ory with an inference runtime of under 50 ms ...
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#48On the Sensitivity of Adversarial Robustness to Input Data ...
that for binarized MNIST with adversarial training, the clean accuracy and the robust accuracy are almost the same. Indicating that getting high robust ...
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#49FP-BNN: Binarized neural network on FPGA - Department of ...
We evaluate the FP-BNN accelerator designs for MNIST multi-layer perceptrons (MLP), Cifar-10 ConvNet, and AlexNet on a Stratix-V FPGA system. An inference.
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#50FPGA implementation of binarized perceptron learning ...
For a simple case study, the proposed learning hardware trains using simplified a MNIST data set for a 25-input binarized perceptron.
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#51How to improve digit recognition of a model trained on MNIST?
@Micka I'm using the preprocessed (binarized, inverted, dilated) version. Ones that match the MNIST training set. There are examples of number " ...
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#52Verifying Properties of Binarized Deep Neural Networks
that creates a representation of a binarized neural network as a Boolean formula. ... a set of experiments on the MNIST dataset and its variants.
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#53izhangh/iRBM - Giters
Training a model (infinite RBM) on binarized MNIST. python train_model.py --name "best_irbm_mnist" --max-epoch 100 --batch-size 64 --ADAGRAD 0.03 irbm ...
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#54ttic31020-MM-mnist-digit-classification | Kaggle
The dataset is available under Data (datasets-ps4.h5). The features are 576-dimensional as before, but are binarized (as mentioned above). Please refer to the ...
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#55Robust Digital Molecular Design of Binarized Neural Networks
We first demonstrate our design on the MNIST classification task by simulating the system as idealized chemical reactions.
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#56Kanerva++ at ICLR21 - Data mining and machine learning ...
... resulting in new state-of-the-art likelihood values on binarized MNIST (≤41.58 nats/image) , binarized Omniglot (≤66.24 nats/image), ...
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#57Training Binarized Neural Networks Using MIP and CP - TSpace
Our experimental results on the MNIST digit recognition dataset suggest that—when training data is limited—the BNNs found by our hybrid approach generalize ...
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#58IN SEARCH FOR A SAT-FRIENDLY BINARIZED NEU
Binarized Neural Networks are an important class of networks ... Published as a conference paper at ICLR 2020. BNNs. MNIST. FASHION. MNISTBG.
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#59The test data, code and detailed description of the AW t-SNE ...
Datasets: This folder contains two datasets, the MNIST dataset and the ... of 1000 groups of binarized MNIST data using aw t-sne algorithm ...
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#60CSE 599i (Generative Models) Homework 2
with discrete outputs for the binarized MNIST dataset, using the training framework found in binaryvae.ipynb. This dataset consists of 28 × 28 ...
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#61Steep Deep Spiking Networks - OSTI.GOV
Data conversion. ▫ We need to convert inputs to spikes. ▫ Binarized MNIST. ▫ Image contours. ▫ Direct current injection.
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#62FINN: A Framework for Fast, Scalable Binarized Neural ...
Competitive results on three smaller benchmarks. Key computation: binary matrix multiplication. Page 6. Binarized Neural Networks (BNNs). MNIST.
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#63Can Attention Masks Improve Adversarial Robustness? - Amir ...
discretization can be used to make classifiers for MNIST highly ... training a DNN with binarized MNIST images (where each pixel.
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#64Single-pixel sensing with optimal binarized modulation
The effectiveness of SPS is experimentally demonstrated on the classification task of the handwritten MNIST dataset, and 96% classification ...
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#65Assignment 3 - Raj Patel
toencoder on binarized MNIST digits, as introduced by the paper Auto-Encoding Variational. Bayes by Kingma and Welling (2013). using Flux.
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#66Can't get accuracy in own digit image dataset for mnist - Stackify
This is because L2normalization is more sensitive to nonzero values. In MNIST samples, almost binarized, i.e. either 0s or 1s. However, in a grayscale image, ...
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#67MNIST by zip - Andreas Kirsch
Confusion matrix for the zip compression classifier on MNIST's test set. Binarized MNIST. If we binarize the dataset by thresholding on 128 ( ...
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#68Applying Convolutional Neural Network on mnist dataset
mnist dataset is a dataset of handwritten images as shown below in the image. We can get 99.06% accuracy by using CNN(Convolutional Neural ...
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#69Handwriting recognition - Wikipedia
Handwriting recognition (HWR), also known as Handwritten Text Recognition (HTR), ... Preprocessing usually consists of binarization, normalization, sampling, ...
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#70Simple MNIST convnet - Keras
Model / data parameters num_classes = 10 input_shape = (28, 28, 1) # the data, split between train and test sets (x_train, y_train), ...
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#71Handwritten text recognition opencv. In the area
When starting with Machine Learning, MNIST Handwritten number recognition comes ... functions to an OCR pipeline such as text segmentation and binarization.
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#72Wandb init mode. We will be using GPU accelerated
... Data pre-processing: build vocabularies and binarize training data. store) – A store ... 1 input and 131 output. keras import WandbCallback mnist = tf.
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#73Mnist visualization - Natale – pre & post parto
Jan 10, 2020 · The MNIST dataset “Visualizing is daydreaming with a ... of 1000 groups of binarized MNIST data using t-sne algorithm.
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#74USA
Abstract: Binarized Neural Networks (BNN) provide efficient implementations of ... MNIST: Both CNN models exceeded the TV- The geometry of binarized objects ...
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#75MNIST handwritten digit database, Yann LeCun, Corinna ...
Make copies!` The MNIST database of handwritten digits, available from this page, has a training set of 60,000 examples, and a test set of 10,000 examples. It ...
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#76Engineering Dependable and Secure Machine Learning Systems: ...
Binarization removes almost all the adversarial noise. as a de-noiser for the ... [11] showed that training a DNN with binarized MNIST images (where each ...
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#77How to Develop a GAN for Generating MNIST Handwritten Digits
How to Develop a Generative Adversarial Network for an MNIST Handwritten Digits From Scratch in Keras Photo by jcookfisher, some rights ...
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#78Data Sets for Deep Learning - MATLAB & Simulink - MathWorks
The MNIST data set consists of 70,000 handwritten digits split into training and test partitions of 60,000 and 10,000 images, respectively.
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#79Machine Learning and Knowledge Discovery in Databases: ...
... drawn from XCNets and CNets learned on the first 10000 samples of a binarized version of MNIST with fixed parameters δ = 50, α = 0.01, and σ = 4.
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#80Machine Learning: A Probabilistic Perspective
0.12 0.14 0.12 0.06 0.13 D2903 E9700 0.07 0.05 0.15 0.07 0.09 Figure 11.5 We fit a mixture of 10 Bernoullis to the binarized MNIST digit data .
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#81Probabilistic Machine Learning: An Introduction
114 19 Figure 9.7 : Visualization of the predictions made by the model in Figure 9.6 when applied to some binarized MNIST test images .
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#82Trends in Artificial Intelligence Theory and Applications. ...
We refer to this version of binarized MNIST as M1. Furthermore, to investigate the effect of increasing the number of features on indexing, we repeat the ...
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#83Morpho-MNIST: Quantitative Assessment and Diagnostics for ...
While MNIST was originally constructed to facilitate research in image classification, in the form of recognising handwritten digits (LeCun et al., 1998), it ...
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#84MNIST demo using Keras CNN - Databricks
datasets import mnist in the previous cell: The purpose of this notebook is to use Keras (with TensorFlow backend) to automate the identification of handwritten ...
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#85MNIST 變識練習 - iT 邦幫忙
[第23天] Tensorflow MNIST練習(1) ... MNIST是機器學習裡面非常重要的手寫數字資料集，如今車牌變識已經如此廣泛! ... 55,000 筆的training data (mnist.train)
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