All Questions

As presented in the first article of Google Wavenet (https://arxiv.org/pdf/1609.03499.pdf) the model can approximate the joint probability of the whole sequence (raw audio waveform) using the chain ...

in short how to set graphs in same coordinate system, not separated as in pic each in its own coordinate system in one frame....

I want to plot the graph with datetime . I saw so many questions similiar to my questions. But that answers didn't work for me. Here is the code that I used: ...

I'm writing my own CNN code from scratch. Though I got fast, converged and satisfactory results, the trained weights change very little in value (while cost/loss function drops in time rapidly in a ...

Does training a pre-trained model on a the same dataset but with sizes scaled down (e.g., by 70%) improve inference speed? More generally, does training a CNN on smaller images improve inference speed?...

Recently I started reading more about NLP and following tutorials in Python in order to learn more about the subject. I started experimenting with words embeddings also, and I found some interesting ...

I have 1000 of datasets within which clustering needs to happen in each of them to find the textual categories. I have vectorized the data using google sentence encoder. What can be the best way to ...

is there any package in python similar to tidyr in R? Except Pandas

Suppose that the utility matrix contains ratings of user on movies. How does matrix factorization find ratings for unobserved (user, movie) pair. Even though the purpose of the algorithm is to find ...

I'm using keras to train a binary classifier neural network. To shuffle the training data I am using shuffle function from scikit-learn. I observe that for some shuffle_random_state (seed for ...

The essence of the problem I want to model is to go from input sequences(length n) to a "distance matrix"(nxn). Although for this distance matrix we are not actually predicting $n^2$ values because it ...

What is the difference between SVM classification error, SVM margin error, and SVM total error ? Is there any clear definition for them ? And what is C parameter in SVM ? Its totally confusing me !!!

Let's say I want to have a bunch of images of hats from videos. How would I priniciple build something that would learn to recognize, and crop or bound box hats? I heard you need a dataset with ...

Can anyone please explain PDF and CDF in simple words. (Please don't define it from wiki.)

I have to resize some images of different size to 224x224 before they can be passed as input for VGG19, and then apply ...

I have for a few weeks measured the time it takes for a product to be released through a automated release pipeline. I have several different categorical features such as "Product Category", "Product ...

I tried to standardize the training data with samples of 629,145 rows and 24 features: ...

Getting a error when trying to import tensorflow library for tensorflow gpu help ...

Consider an unsupervised data. The data is in the form of a csv file( I am using pandas dataframe for this). Its a web page data at different time steps and the way I am converting data to be fed to ...

I'm working on a project about recognizing moroccan license plates which look like this image : Moroccan License Plate Please how can I use OpenCV to cut the license plate out and Tesseract to read ...

I have the aim to build a model to predict global horizontal irradiance (ghi) using satellite images and other features namely the day of the year and time of the day. For extracting the satellite ...

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I'm using an autoencoder-RNN combination to predict colliding waves in 1D. The training data is obtained by using the 1D Euler equations along with boundary conditions to preduce to waves (left and ...

I want to implement the following algorithm, taken from this book, section 13.6: Here, the neural networks' outputs are $V(S, w)$ and $\pi(A|S,\theta)$, parameterized by $w$ and $\theta$ respectively....

I have a dataframe that contains product and in this dataframe I have some features like: brand, cat1, cat2, ...

our data set has missing values. Further examination tells you that they are spread along 1.5 standard deviation from the median with distribution mean = 0 & variance = 5. How much data would ...

I'm learning linear regression, and I ran a step function for linear regression and checked out the residuals vs fitted plot for the final equation. The residual looks homoscedastic but it's not ...

I want to view a specific image or a dataset's distribution, and see if they are different. Does simply writing something like : ...

I'm trying to perform a large image dataset clean up (filtering all the minors\babies from it). My initial approach was to utilize age detector, such as https://github.com/deepinsight/insightface/...

In linear regression, we are fitting a polynomial to a set of data points. In Bishop's book of Pattern Recognition & Machine Learning, there are a few examples where the fit is a curve or a ...

I am reading a book (TensorFlow For Dummies, Matthew Scarpino), and here it says: Adagrad methods compute subgradients instead of gradients. A subgradient is a generalization of a gradient that ...

I intend to display confusion matrix using Keras while K-fold of scikit-learn. My code using Keras is: ...

I am looking for a large image dataset >20K to be used for cancer classification algorithm. Where can I look given that all public available datasets are maximum 1K in size which is much less than ...

In the paper "Attention is all you need" the authors add a positional encoding to each token in the sequence (section 3.5). The following encoding is chosen: $ PE(pos, 2dim) = sin(pos / 10000 ^ {2dim/...

It turns out that many things behave very differently in high dimensional space. The below paragraph is picked from a book. I need extra help to understand. The book says, if you pick a random ...

In the context of deep-learning, I understand why the test or validation error can go up with more training: this is the result of overfitting. I also can think of one reason why even the training ...

Are there libraries available or does one have to write these functions from scratch.

I run Boruta with RandomForestClassifier the previous day on my data (nb features = 36) and got 17/36 confirmed. Now I run it again and there is 0/36 and stop at the 9th iteration. Any idea why this ...

Blockquote I have been coming across function calls that use arguments that are not in the function definition. I would like to know how that works (i.e. how the compiler interprets this). For ...

I have continuous (time series) data. This data is multivariate. Each feature can be represented as time series (they are all calculated on daily basis). Here is an example. ...

Could someone please explain to me how and why can we go from equation $4.3$ to equation $4.4$: $$\hat{c}= \arg\max_{c \in \mathcal{C}}P(c|d) = \arg\max_{c \in \mathcal{C}}\frac{P(d|c)P(c)}{P(d)}\tag{...

I have a dataset that contains information of pets (Breed,color,age,some text descriptions) and images of that pet. One pet can have more images than others. I want to combine these images somehow to ...

I am sometimes in the following situation: I want to execute two cells: Cell 1 takes on the order of 10 minutes or hours. Cell 2 will take 1 second. I'd rather execute cell 2 first and see the result,...

I designed a specific Convolution Neural Network to study in the area of image processing. The network has a part that there are two tensors which have to be transformed into a tensor in order to be ...

I am working with a small dataset ( N = 50 ). I would like to normalise my input features. I am facing the following issues: Because of the small size of the dataset the range of training input ...

Can somebody please explain intuitively why the variables need to be orthogonal to each other? Does orthogonality imply independence? When the variables are independent then we get an estimate using ...

We are running RandomForest model on a time-series data. The model is run in real time and is refit every time a new row is added. Since it is a timeseries data, we set shuffle to false while ...

Hello fellow machine learners, We have numerous pairs of 64 x 64 (or other dimensionality) images (maps). In each pair, the first image demonstrates a physical parameter, e.g. wind speed, at each ...

I am trying to learn how to make an LSTM in keras and I was having difficulty working out what input dimensions the data needs to be for the cudnnlstm layer. Each time I try to alter the input_shape I ...

Judging by the negative result being displayed from my ridge.score() I am guessing that I am doing something wrong. Maybe someone could point me in the right direction? ...