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30 views

I am obtaining a ValueError regarding the input arrays and there dimension. I am trying to create a Random Forest Regression Model for price prediction using both numerical features and categorical ...
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65 views

however my cost is continuously decreasing but my linear regression is unable to predict just simple pattern y=x+5. i tried all value for alpha and minimum cost i got is 3.00. x=[] y=[] for i in range(...
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1 answer
26 views

I am running some Machine Learning algorithms in order to train a model. Until now I've been doing a correlation matrix in order to select the characteristics with highest correlaction to my target ...
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1 answer
90 views

I am currently working on an image classification task, and the process involves training with the desired target values, making it a supervised learning task. However, when training a model, such as ...
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0 answers
23 views

My Code (from coursera): def gradient_desc(X, Y, w_in, b_in, cost_f, grad_f, alp, num, lambda_): m = len(X) # An array to store cost J and w's at each iteration primarily for graphing later ...
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105 views

I'm working on training an NLP model to detect sensitive information in documents. There are 15 categories of sensitive information I'm attempting to predict. It seemed like adding another category ...
1 vote
2 answers
960 views

I am trying to write a simple code to teach resnet50 on ImageNet dataset. I don't quite get why normalization does not work. When I use this transformation as data augmentation: train_transforms = ...
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1 answer
200 views

I have used CLIP embeddings of image and text as the input and the output is a label ranging from 0 to 5 (6 way label). I tried to make an implemention of this multimodal 6 way classification using ...
0 votes
1 answer
72 views

The Bayes estimator uses p(x, y) as a probability mass function over (X, Y ) where X = [n] and Y = [k] thus for every x∈X and every y∈Y, p(x, y) = 1. There is a k x k dimension cost matrix, C ∈ [0,∞) ...
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0 answers
67 views

I try to code a semi-supervised model for a project besides the university. First I got a model which trained with the model.fit (I tested the model with supervised learning first). But for semi-...
1 vote
1 answer
436 views

I have two datasets, one numeric and one semantic information of the numeric ones. I want to train an autoencoder to give latent embeddings that should match the semantic dataset. That is: ae_model = ...
-1 votes
1 answer
309 views

I have a classification problem to figure out hotel cancellations (in python). I'm stuck in a problem of the first steps. I have some variables regarding hotel reservations, and some of them are: ...
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2 answers
66 views

I have two folders, each folder contains words in various .txt files, one folder is named 'good' while the other is named 'bad', I want to write a python script that will import all the data into a ...
1 vote
1 answer
325 views

Consider the following model modeling nine genotypes (integer numbers) by their growth pattern (The ratio of plant height growth over plant diameter growth) over time (in day of the year). m2 <- ...
3 votes
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204 views

In an image classification task of around 15 classes, the classes are rathe simple, categorized by color. Not some very high level detail. The graphs of loss and accuracy over 100 epochs I am using ...

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