Category : training-data

I have a question regarding the use of UUID identifiers when doing machine learning. Let’s say I’m building a collaborative filtering based movie recommender using a version of the MovieLens dataset. However, instead of having the user IDs as integers, I’m using UUIDs. For training, I can process the data in at least a couple ..

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I’m using Google Vision OCR for blood results. Users can take picture of their blood results and my job is to extract meaningful informations. For example, in the picture below, I might want to extract the number related to the TSH (here: 0.722). Example: But the pictures I get are never that straight, they are ..

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I’m trying to convert my pytorch model to pytorch lightning, and I couldn’t find any example similar to my own online to confirm. This is my model: import torch import torch.nn as nn from resnet import ResNet, Bottleneck class KeyPointDetector(ResNet): def __init__(self, **kwargs): super().__init__(Bottleneck, [3, 4, 6, 3], **kwargs) self.conv1 = nn.Conv2d(1, 64, kernel_size=7, stride=2, ..

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I am working on a classifier project based on udemy course(Deep Learning Computer Vision™ CNN, OpenCV, YOLO, SSD & GANs) The system i use has configuration below: Corei7 CPU, 32GB RAM, windows10, gtx1060 by 6GB Memory GPU, msvc 2019, tensorflow 2.4.0, cuda toolkit 11.0, cudnn 8.0 (the config is set based on tensorflow official website ..

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I am working on APML (severe type of Blood cancer) Detection, a classification problem, I collected data from real environment which is imbalanced. I have just 31 samples for positive class and 574 samples for negative class. I build an SVM model, but not getting good results. I have also tried PCA, up sampling and ..

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I’m running into an incompatible shapes error that I am not able to trace. I’m trying to use the code provided here: https://data-flair.training/blogs/face-mask-detection-with-python/ and I’m working on google colab. I’m at step 5 where I train the model with model.fit_generator() which is where the [10,2] vs [10,3] error happens, Using fit() gets the same error. ..

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