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I aim to generate a value from multivariate time-series data. To be more clear, an example: ...

I'm working on my chess bot, and I would like to implement simple artificial intelligence for it. I'm new in it, so I'm unsure how to do it specifically on chess. I heard about Q-learning, Supervised/...

I have read a number of papers on Yolov5 images detection techniques. But the papers don't refers to any segmentation step done by Yolov5. While I know that it is not possible to do image ...

I'm using a pretrained resnet50 for faster RCNN to detect areas with 2 classes (background and interest class). As part of my data inputs for training, I have background images without any annotation ...

I am using the WGAN implementation provided here: https://keras.io/examples/generative/wgan_gp/ And I wanted to save the GAN and its components. When I do wgan.save("my_folder") I get: ...

I want to train a network with mBART model in google colab , but I got the message of ...

Do I have to apply PCA after pre processing the dataset or prior to pre processing ? After pre processing(encoding) the data the number of columns is increasing to over 100 so should I be reducing the ...

I am attempting to implement my own Ridge Regression algorithm and I am trying to achieve similar coefficients found in a MATLAB tutorial on regression. Specifically, on the MATLAB tutorial page you ...

I have gone through the process of filtering a set of data that I have by removing excess numbers and values that are invalid. However, there is a lot of data that occasionally has ' ' in it, and ...

How can I measure or find the time complexity for a model and memory complexity like VGG16 or Resnet50 also and does it will be different from one machine to another like using GTX or RTX?

I have a deep learning model in TensorFlow with a single output. For the training instances, I want the mean of output to lie in range. How can I implement this constraint in TensorFlow?

I have previously trained a YOLO v4 object detection model and I am looking to leverage the results(Bboxes) of this model and create another model to recognize/classify accidents in CCTV footage/video(...

So a little bit of a background: I have a folder which contains video files of lets say humans doing a certain action (i.e. walking) where each .2 seconds is documented in a ...

I'm trying to do a superresolution network, but I am having trouble importing my own data. I have two types of images: resized images (smaller), original images. The first one is going to be used as ...

Given a set of retail stores with specific attributes, as well as store level sales data, what would be a good way to determine the most important drivers of sales?

I am running five different regression models to find the best predicting model for one variable. I am using a Leave-One-Out approach and using RFE to find the best predicting features. Four of the ...

After checking out this similar post for python: Best python library for neural networks, I was curious if the community had recommendations for JavaScipt modules for creating neural networks. I am ...

I'm running some experiments to examine the results of teaching various kinds of pretrained models new words, and seeing whether they generalize these new words to different structures based on the ...

can anybody please provide me the solutions in layman language, how a deep learning network works. ...

I wondered if anyone was aware of research and corresponding R packages based upon unsupervised clustering in two different states. For example, suppose I have a panel data sample with 12 ordinal ...

I'm quite new to the field of deep learning. While i've trained several smaller deep models on varies public datasets, i now have a problem with my variational autoencoder. Task: I have a 3D-tensor ...

I am working on fraud detection on blockchains. To be more specific, I fetched a big number of transactions that took place on the blockchain, labeled them to spam / non spam using an appropriate API ...

I have the following question: What does the sample covariance between a quantitative variable and a binary encoded variable tells us? And would it make sense to include the binary variable in a ...

I have a dataset that consists of 700 categorical columns and around 6000 rows. I created 2-50 clusters with the k-mode algorithm and plotted the cost function to determine the optimal number of ...

I have multiple json files in a folder called "app users". These json files has NAN values as well in it.

I have tried using MSE on Resnet50 for the CIFAR10, no matter how I change the output layer like dense(1, relu)/dense(1, sigmoid). The model failed to converge in the training. What is the correct way ...

I have searched a lot for this issue but unfortunately came up with nothing. Usually in a ML model, during preprocessing, we use Pipelines and ...

What kinds of machine learning tool is used to classify a vector of data which are not spatially correlated? I have a 158*158 image*15000 samples which I tried to ...

I want to cluster the data points into 2 clusters. For that, I used a deep neural network but I have no labels to backpropagate. How can I backpropagate? which loss function I can use in this problem ...

Good Morning. I am working on an assignment where i need to perform the following tasks: 1.Create 500 observations based on standard normal distribution and store them in variable X 2.Create 500 ...

I am new to data science. I am attempting to write a program using regression techniques, and all of my values are numerical, except for the date and time (UTC), which are written in this format: HH:...

I am writing a program that will take a multitude of data, such as chlorophyll levels, water temperature, nitrogen/phosphorous levels, etc., in order to predict the growth of algae in a body of water. ...

We know that there are many different types of classification algorithms. But among the different categories of classification algorithms, which algorithms are suitable for binary classification and ...

My CNN tensorflow model reports 100% validation accuracy within 2 epochs. But it incorrectly predicts on single new images. (It is multiclass problem. I have 3 classes). How to resolve this? Can you ...

I am using keras LSTM to predict a seq2seq of 2 variables. I have test results for 50 subjects with ±20 tests per subject. the data is a 2 variable sequence with shape (101,2). as you can see, the ...

I have an deeply understanding-problem with Random Forest Regression. Target is a university project: We have to do a random forest regression analytics with financial data in R. I already read many ...

We're struggling with memory usage in a project that deploys multiple models to the same GPU (models are usually built with PyTorch and TensorFlow). It was suggested that we could use ...

Context I am working on a regression problem trying to predict affordability. My dataset contains daily installments repaying a purchase in a form of contract. Essentially, a minimum daily rate the ...

I have two kinds of data with several categories and multiple variables. I have done a MCA analysis on both of them to reduce the dimension. Now, would like to make a cluster analysis combining both ...

While studying some (pytorch) examples that use pretrained GloVe vectors I came across two variants: Use the vocabulary of the GloVe vectors and thus initialize the embedding layer with the ...

I am working on a topic modelling task. I want to convert different parts of speech such as adjectives, verbs to noun. What are the best ways of doing this? I have tried lemmatization using NLTK ...

I'd like to use a feature store to store some time series and I asked myself what's the best way to store the timesteps. Is it better to store each timestep horizontal and then doing windowing after ...

I am trying to regress over very small floats - of the magnitude [1e-2, 9e-3]. They're mostly in this range. Using simple ...

I had a data set that I am trying to carry out a regression for. I have created this command however I get the following error message on running it. ...

I have a dataset that has some unique values but also includes information from multiple individuals that are repeating, meaning they are describing the same attributes and can have the same or ...

Currently, I am studying the third chapter of An Introduction to Statistical Learning with Application in R which discusses linear regression. In section 3.6.5: Non-linear Transformations of the ...

If my dataframe looks like this: ...

Typically for a ML workflow, we import the data (X and y), split the X and ...

How can I identify whether the training data and test data came from same distribution or not? I tried with TFIDF and cosine similarity ...

(cross posted from main stackoverflow) This is a weird situation so I hope I can explain it correctly. My partner and I are working on a ML project where we create a model that predicts whether a ...