I am working with a dataframe structured like this: id amenities ... 1 "TV,Internet,Shower,..." ... 2 "TV,Hot tub,Internet,..." ... 3 "Internet,Heating,Shower..." ... ... My goal is to split the string by comm ...
The issue I am attempting to address is more complex than it appears. To simplify the problem, I have created a simple game that serves as a precursor to solving the larger problem. Starting with a 5x5 matrix where all values are initially set to 0: stru ...
Having recently ventured into the realm of machine learning, I'm faced with a challenge in applying it to my specific problem. My training dataset consists of 44000 rows of features with a shape of 6 by 25. My goal is to construct a sequential model, but I ...
Looking to implement the YOLO object detection Model? I have successfully annotated my images and have them in coco format. I now have a Json file containing label annotations for the train, test, and valid data sets. When defining the model's confi ...
Currently, in my journey to learn machine learning, I am utilizing Python on Jupyter notebook. Oftentimes, I encounter the issue of waiting endlessly for results after running my code. This leaves me questioning whether my script is actually executing or ...
I am currently working on a Decoder with an output shape of (None,32,32,1). However, the following code snippet shows a decoder with an output shape of (None,28,28,1): # Decoder latent_dim = 2 latent_inputs = keras.Input(shape=(latent_dim,)) x = layers.Den ...
Is there a way to compare the column names of two separate Pandas data frames? Specifically, I am interested in comparing the columns between my train and test data frames. There are some columns missing in the test data frame that I need to identify. ...
To verify my code, I can use the following line: print(regressor.predict([[1, 0, 0, 90, 100]])) This will generate an output. The first 3 elements in the array correspond to morning, afternoon, and evening. For example: 1, 0, 0 is considered as morning 0 ...
I am currently working on developing an image classification model to identify different species of deer in the United States. As part of this process, I am utilizing Principal Component Analysis (PCA) to reduce the memory size of the images and optimize t ...
I am facing a challenge while creating a keras model with multiple input branches as the inputs have different sizes, resulting in an error message from Keras. Below is an example showcasing this issue: import numpy as np from tensorflow import keras fro ...
Currently, I am in the process of training a binary classifier using python and the well-known scikit-learn module's SVM class. Upon completing the training phase, I utilize the predict method to classify data based on the guidelines outlined in sci-kit's ...
Can the torch.nn.Embedding function process a one-hot vector ([batch_size, seq_len, vocab_size]) to produce embeddings equivalent to those generated from an input of integer tokens [batch_size, seq_len]? And if so, would this process be differentiable? ...
I am looking to streamline the database creation process by utilizing a CSV file that contains 160 columns and 15 rows of data. Manually assigning names for each column is proving to be quite challenging due to the large number of columns. I have managed t ...
Currently digging into the Titanic dataset, I've been experimenting with applying an SVM to various individual features using the code snippet below: quanti_vars = ['Age','Pclass','Fare','Parch'] imp_med = Sim ...
My dataset contains a mix of categorical and non-categorical values. To handle this, I used OneHotEncoder for the categorical values and StandardScaler for the continuous values. transformerVectoriser = ColumnTransformer(transformers=[('Vector Cat', OneHot ...
I am currently exploring the connection between the sklearn's .fit() method and the .predict() method. I have not been able to find a comprehensive answer to this question on other online forums, although similar topics have been discussed (see here). Whi ...
My dataset contains two columns: procedure name and corresponding CPT codes. There are 3000 rows with a total of 5 classes of CPT codes. As part of my project, I am working on building a classification model using this data. However, when providing input ...
I am currently delving into the realm of machine learning and working on constructing an LSTM neural network. My model takes in 7 features as input and aims to predict 2 labels. However, I encountered an error when passing all 7 inputs into the LSTM laye ...
Currently, I am in the process of training a GAN using Google Colab with a dataset of images sourced from Wikiart that have been converted to 1024x1024 resolution. However, I keep encountering an error when attempting to create the tfrecords: Traceback (mo ...
During my attempt to implement a gradient descent algorithm, I encountered an intriguing issue related to the ineffective use of **kwargs. The function in question is as follows: def gradient_descent(g,x,y,alpha,max_its,w,**kwargs): # switch for v ...
Currently, I am exploring the use of sklearnex/scikit-learn-intelex for GPU acceleration. The code snippet below is what I have implemented based on the instructions provided in 'Patching several algorithms': try: from sklearnex import patch_sklearn ...
It seems like the error is related to an issue with shapes, but pinpointing the exact source has been challenging. The error message advises trying the following: Also, consider using the tf.function experimental_relax_shapes=True option to relax argum ...
Is it possible to achieve a specific dimension when using the MultiLabelBinarizer in sklearn? For instance, given the following code: from sklearn.preprocessing import MultiLabelBinarizer y = [[2, 3, 4], [2], [0, 1, 3], [0, 1, 2, 3, 4], [0, 1, 2]] MultiL ...
Currently, I am in the process of developing a predictive model using linear regression on a dataset containing 157673 records. The data is stored in a CSV file and follows this format: Timestamp,Signal_1,Signal_2,Signal_3,Signal_4,Signal_5 2021-04-13 ...
I have been using scikit-image to successfully classify road features. Take a look at the results here: https://i.stack.imgur.com/zRJNh.jpg. However, I am facing challenges in the next step of classifying these features. Specifically, I need to classify fe ...
In my quest to discover the nearest neighbors for a dataset A containing 25,000 rows, I have ventured into fitting dataset B into a KNN model consisting of 13 million rows. The ultimate objective is to identify 25,000 rows within dataset B that closely res ...
Clarifications: This question pertains to the QuickDraw RNN Drawing classification tensorflow tutorial, and not the text RNN tensorflow tutorial While similar to Farooq Khan's question, further specific details are required, hence this query. Acknow ...
Imagine we are working with a time-series dataset that shows the daily count of orders over the past two years: https://i.stack.imgur.com/vI2AA.png To predict future orders, Python's statsmodels library can be used: fit = statsmodels.api.tsa.statespace.S ...
I am working with a unique document It's not your typical text It's full of scientific terminologies The content of this document looks like this RepID,Txt 1,K9G3P9 4H477 -Q207KL41 98464 ... Q207KL41 2,D84T8X4 -D9W4S2 -D9W4S2 8E8E65 ... D9W4S2 3,-05L8 ...
My partner and I are collaborating on a project to create a model that can classify images based on whether or not they show someone wearing a mask correctly. However, we're encountering an issue when trying to run our model - a ValueError keeps appea ...
In an attempt to cluster data based on object names, x_coordinate, y_coordinate, and corresponding temperature, I am experimenting with the mean square clustering algorithm. The goal is to group nearby objects according to location and temperature in order ...
Every time I try to run this TensorFlow code for GAN, I encounter an index error of "list index out of range." import pandas as pd import numpy as np import tensorflow as tf import time dataset = pd.read_csv('kagglecreditcard.csv') is_Class0 = dataset[ ...
Within Sklearn, the n_jobs parameter is utilized in various functions to specify the number of cores to be used. This allows users to dictate the amount of processing power allocated for a specific task; for instance, inputting 1 uses one core while -1 s ...
Encountering an error while chaining the estimators and attempting to view. As a newcomer to Python, this was my first time experimenting with the pipeline function. from sklearn.pipeline import Pipeline from sklearn.linear_model import LogisticRegression ...
While attempting to serve a model in Databricks using MLflow, I encountered the following error: Unrecognized content type parameters: format. IMPORTANT: The MLflow Model scoring protocol has changed in MLflow version 2.0. If you are seeing this error, y ...
I have a dataset containing 4000 CNN features for a binary classification problem. The only information I have about the test data is the proportions of labels 1 and 0. How can I instruct my model to predict test labels based on these proportions? Is there ...
Encountering some unusual errors while using the LassoCV() regressor with a grouped cross-validation object. To be more specific, when working with dataframe df and target column y, I want to conduct LeaveOneGroupOut() cross-validation. When I try the fol ...
I am faced with a challenge in Python where I have two lists of values and need to calculate the shortest distance between each pair of points from the first list. list1 = [(10,15),(40,50),(10,60)] list2 = [(12,17),(38,48),(12,63),(11,17),(10,59)] My tas ...
In my current project, I am using the MS-COCO dataset to work with images. My goal is to extract bounding boxes and labels for images containing backpacks (category ID: 27) and laptops (category ID: 73). These annotations will be stored in separate text fi ...
I am in possession of a large JSON dataset containing English conversations and I am curious about potential tools or methods that could facilitate translating them into Arabic. Are there any suggestions? ...
Looking to conduct document clustering using JSON String data containing various key-value pairs of String and Number types. The goal is to cluster documents based on similar types of keys and values. For example, consider the following JSON Document: {" ...
I am currently working on implementing a batch normalization layer using tensor-flow. When it comes to running the training step with tf.moments to calculate the mean and variance, everything works smoothly. However, for testing purposes, I want to introd ...
Currently, I am working on implementing a classification algorithm using a dataset related to medicinal research. My main focus is to achieve good recall in disease recognition. In order to do so, I had the idea of creating a scorer like the following: re ...
Even though I provided all the necessary code, including the Flask app, predictionmodel.py, and HTML code, I am still encountering an error when running it locally after clicking submit. The browser (or proxy) sent a request that this server could not un ...
I am interested in creating a neural network using keras, sklearn, and tensorflow to predict the (n+1)-th value for a given dataset in a 1-dimensional array. For example, if I have [2,3,12,1,5,3] as input, I would like the output to be [2,3,12,1,5,3,x]. H ...
Seeking Assistance! Thank You in Advance for your help. I am currently working on creating an object detector using Python in Google Colab. I'm facing some issues and would greatly appreciate your guidance. Could it be a module version error or perha ...
Looking for a way to save the weights of a PyTorch model into a .txt or .json file? One method is to write it to a .txt file using the following code: #import torch model = torch.load("model_path") string = str(model) with open('some_file.txt', ' ...
Having recently delved into the realms of keras and machine learning, I am experiencing some issues with my code that I believe stem from my model. My objective is to train a model using a CSV file where each row represents a flattened image, essentially m ...
Is there a way to predict the production of fields for the years 2018 and 2019 at various locations using a small amount of data? By utilizing historical data, it is possible to forecast the production of fields at each Harvesting Site identified by index ...
Having an issue trying to extract the image of rock, paper, scissors and ensure the output matches the picture. I attempted to obtain a matrix representation, such as [1,0,0] for paper, [0,1,0] for rock, and [0,0,1] for scissors. However, upon reaching the ...
from sklearn.model_selection import cross_validate scores = cross_validate(LogisticRegression(class_weight='balanced',max_iter=100000), X,y, cv=5, scoring=('roc_auc', 'average_precision','f1','recall','balanced_accuracy')) scores['t ...
As a newfound web application developer, I have already developed several applications. Lately, I have noticed the increasing value of Machine Learning, Deep Learning, and NLP. I am eager to learn how these technologies can be applied to web applications ...