Questions tagged [bigdata]

Big data is the term for a collection of data sets so large and complex that it becomes difficult to process using on-hand database management tools or traditional data processing applications. The challenges include capture, curation, storage, search, sharing, transfer, analysis and visualization.

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14 views

How to choose feedforward architecture for few number of features but very large instance?

Assume I have 1 million of data instance and each instance contains 100 feature. For each instance, I also have a lable. The ...
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Examples of Open source huge business intelligence datasets

I've observed that many of the datasets available for traditional ML and data science algorithms seem to be in the order of MB. I assumed these may be because earlier computers were not that ...
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14 views

XGBoost incremental training for big datasets

I am trying to train an XGBoost model on a quite big dataset (tens of GB, almost a hundred). I have been trying to use some libraries such as Dask to deal with this problem, without any success due to ...
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11 views

What are the execution service and the event service in Netflix big data

From the following article by the netflix engineering team: The core architecture of the big data platform at Netflix involves three key services. These are the execution service (Genie), the ...
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20 views

How do you do 1-vs-rest classifiers in XGBoost Library (Not Sklearn)?

I am working with a very large dataset that would benefit from using training continuation with the xgb_model parameter in ...
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1answer
20 views

Subsampling the “right” amout of data to train an ML model

I am training a machine learning model (i.e., a classifier) on a large dataset. I know that I can get the same results using less data (about 30%) but I would like to avoid the trial and error process ...
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10 views

Scalable Infrence Server for Object Detection

I have created a Django service (nginx + Gunicorn) for object detection models. For my case i have 50+ models with resnet 50 based back bone. Server Machine Specification: 16 CPU 64 GB Ram I have ...
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21 views

What should be the architecture design for the dataset to be used for a machine learning API

I have aroud 30GB of market dataset in csv format which is downloaded onto my server computer everyday. Now I want to use this dataset to do some computations and provide some analysis. The user will ...
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27 views

How do you perform basic statistical analysis on a Binary Dataset?

I have never worked with a Binary dataset (1 and 0) (True or False) so I'm unsure what kind of statistical tests I should run to draw up simple conclusions. I'm doing a data science project and the ...
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What is the best way (cheapest / fastest option) to train an model on massive dataset (400GB+, 100m rows x 200 columns)?

I have a 400GB data set that I want to train a model on. What is the cheapest method to train this model? The options I can think of so far are: AWS instance with massive RAM and train CPU (slow, but ...
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Working with mySQL and pytorch Dataset

I am working with high frequency time indexed data. We have 2 types of data each with about 5 columns. For each type of data we have 2500 streams coming in and being updated every 1ms-100ms (the ...
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37 views

Extracting possible relationships and insights from a large dataset

I have a dataset with about 26'000 variables and 33'000 continuous observations. My task is to extract any interesting insights/possible relationships between various variables. I am looking for any ...
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How to Combine Oracle and Snowflake/Redshift data on the fly

Have a Schema.Table_Name on Oracle. Exactly similar table is on Snowflake with same metadata(Schema.Table_Name). How can I combine data from two on the fly without moving Oracle data to Redshift. Most ...
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1answer
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Where can I find a dataset that contains criminal case sentencing data? [closed]

I would like to study a dataset where each record represents a criminals case in the US and contains attributes such as: Type of crime Defendant Age/Sex/Race Plea Verdict Sentence Is there a dataset ...
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30 views

In Spark, what's the role of each of Cluster manager and Spark Context?

What's the role of a cluster manager and the role spark context (Driver program) in terms of managing worker nodes. How do they communicate with each other (and with the worker nodes) and when they do ...
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Trigger job in SAP BW from SAC

Is there a way to have the following occur: When a job is finished on the SAC (SAP Analytics Cloud) side, a job on the SAP BW side should be triggered. Is that at all possible? I have found this which ...
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14 views

Difference between MapReduce, Dryag and Pregel in terms of efficiency

What is the difference between the three parallel processing paradigms: MapReduce, Dryag, and Pregel in terms of efficiency for big data analytics applications? Thank you.
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1answer
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What data to collect to create useful insights?

I am creating a Social Media app and I want to know what type of data shall I collect to create useful insights for Business accounts or Content Creators? For example if I want to create an insight ...
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1answer
34 views

How to train a model using a daunting huge training dataset

I have an extremely huge dataset and I'm wondering me how could be the right way to set an experiment to use this data to train a model. I understand that I can use data-reduction to, for instance, ...
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31 views

How to Integrate/map Population Data with/over Sample Data

Problem Definition: Our organization is conducting different type of surveys and Census in our country. The basic difference between Census and Survey is that, the target of Census is the Complete ...
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46 views

Clustering large set of images

I've got some big datasets of images (a few million each), and I would like to cluster them according to images' visual similarities. I've extracted a feature vector for each image; the space of ...
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29 views

What is the difference between Pachyderm and Git?

I learned that tools like Pachyderm version-control data, but I cannot see any difference between that tool with Git. I learned from this post that: It holds all your data in a central accessible ...
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1answer
89 views

Why do machine learning engineers insist on training with more data than validation set?

Among my colleagues I have noticed a curious insistence on training with, say, 70% or 80% of data and validating on the remainder. The reason it is curious to me is the lack of any theoretical ...
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17 views

What is the azure solution for storing and querying Netcdf data on the fly?

We currently run a live web application which utilises standard azure mounted file storage to store 2tb worth of metocean data in netcdf format. On here we run python queries directly on the data e.g. ...
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1answer
30 views

How to grade an interaction that a user had with a post with an AI based on big data?

Context I'm creating a social network. The thing is, I don't want to order posts by likes, or something like that, I'm using an AI (lightfm in ...
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1answer
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How do data types influence hardware (CPU / GPU / TPU) performance?

I am currently dealing with a relatively big data set, for which I have some memory usage concerns. I am dealing with most of the different data types : floats, integers, Booleans, characters strings ...
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21 views

Is there a data structure that works similarly to a (binary) tree?

Im currently working with some data, which is part of a very large data set (height, about 6000 elements per timestep - timestep every minute over days at a time). I need to differentiate between ...
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16 views

How are big models like GPT-3 developed?

For models trained with a moderate amount of data, I would expect a the development workflow to include extensive hyper-parameter optimization through extensive retraining. But how is this handled for ...
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16 views

Ideas on handling large quantities of “waste” data

Hello and thank you for taking time out of your day to help me. I am currently working on developing a machine vision application for production monitoring. The application handles images, about 20,...
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1answer
173 views

How to store efficiently very large sparse 3D matrices

To train a CNN, I have stacked arrays of images over observations [observations x width x length]. The dataset is very sparse ($95\%$). What would be an efficient ...
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33 views

Create User Table from Google Firebase Analytics and Cloud Firestore Collections

I am exporting my snowplow collections collected on Firebase using the extention Export Collections to BigQuery firestore-bigquery-export v0.1.10. Whenever a document is created, updated, imported, or ...
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1answer
202 views

How does skewed data affect deep neural networks?

I'm playing around with deep neural networks for a regression problem. The dataset I have is skewed right and for a linear regression model, I would typically perform a log transform. Should I be ...
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1answer
115 views

Public dataset for news articles with their associated categories for multilabel data classification

I am wondering if there are any public datasets of news, like New York Times (NYT) or similar to various news categories such as politics, entertainment, lifestyle, general news, sports etc. I want to ...
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How much information is produced in our Society? [closed]

I was reading an interesting article about the growth of data in our society: https://rss.onlinelibrary.wiley.com/doi/epdf/10.1111/j.1740-9713.2012.00584.x Does any of you know if there exists a more ...
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15 views

Automatic EDA for BIG Data

I have data set of cicids2017 which in total has 2830743 rows and 79 columns. Since my local jupyter was crashing a lot, SO I am using Google Colab. But Google Colab is also crashing if some big ...
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1answer
104 views

What is the main difference between Hadoop and Spark? [closed]

I recently read the following about Hadoop vs. Spark: Insist upon in-memory columnar data querying. This was the killer-feature that let Apache Spark run in seconds the queries that would take Hadoop ...
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18 views

Looking for the proper algorithm to compress many lowres images of nearby locations

I have an optimization problem that I'm looking for the right algorithm to solve. What I have: A large set of low-res 360 images that were taken on a regular grid within a certain area. each of these ...
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1answer
30 views

How can I predict the true label for data with incomplete features based on the model learned by data with complete features? [closed]

for example, the model was learned by training data with complete features (f1,f2,f3,f4,f5,f6) but, I wonder the model can test data with incomplete features (f1,f2,f3) to attach the true label to ...
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108 views

Does Call Detail Record(CDR) data record different cell-site/tower on incoming and outgoing call/text?

I am working on CDR data to find important locations of user. The data I have does not have coordinates so I will be using cell-site location as user's location. But after doing some working on data I ...
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1answer
738 views

How to determine sample rate of a time series dataset?

I have a dataset of magnetometer sensor readings which looks like: ...
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0answers
159 views

How do I efficiently load data from disk during training of deep learning models in pytorch?

I'm trying to train a deep learning model without loading the entire dataset into memory. My main question is, what's the best way of doing this? It seems like HDF5 is a common method that people ...
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0answers
49 views

Spark: How to run PCA parallelized? Only one thread used

I use pySpark and set my configuration like following: ...
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25 views

What is important for Pharmaceutical companies to answer with Big Data Analysis?

I am a data scientist, and I have some biological background (genetics). I have been asked to give a talk for our customers from pharmaceutical industry. I should show them how they benefit from Big ...
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2answers
30 views

Maximum number of images to train a convolutional neural network

I just wondered if there is a technical limit on the number of images to train a neural network. I want to work with extremely high numbers of images, around 1,000,000 to 10,000,000 images. Is there ...
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1answer
51 views

Training models from sklearn using tf.distribute.MirroredStrategy

I want to distribute the training of a simple model, such as a support vector classifier like sklearn.svm.SVC() across some or all CPUs and GPUs on a single device. I have never utilized a GPU before ...
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1answer
18 views

Suggestion of dataset

I am implementing my own deep network, but I am not so good at calculus so my network only works for binary data in the moment. I have been searching for big tabular datasets that are for binary ...
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9 views

What makes a good image dataset to compare biological NNs to ANNs?

I'm going to be comparing biological NNs to ANNs based on compounded adversarial attacks, but wish to know what makes a good image dataset to test on biological NNs? Going for image classification. I'...
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1answer
51 views

anomaly detection in vehicle sensor data

I am currently diving deeper into understanding more about anomaly detection in regards to vehicle's data generated by sensors. It seems like there is no proper book or article that goes deeper into ...
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1answer
23 views

How to feed key-value features (aggregated data) to LSTM?

I have the following time-series aggregated input for an LSTM-based model: ...
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5 views

Surpassing MongoCompass limit() limitations

I have a cluster containing aproximately 8 million files in json format(tweets). My problem is that when analyzing the schema, I can only visualize 1000 files, no matter what number i enter in the ...

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