cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.ptkchv
title: Occurrence Download

description: A dataset containing 1828 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry MULTIPOLYGON(((-61.34054 -54.64352,-61.3877 -54.64005,-61.43485 -54.63486,-61.48021 -54.62828,-61.52438 -54.61581,-61.5584 -54.60091,-61.59004 -54.58393,-61.6157 -54.56451,-61.63779 -54.54265,-61.68196 -54.50029,-61.68255 -54.49995,-61.68792 -54.49369,-61.71419 -54.4645,-61.74881 -54.43284,-61.75 -54.43192,-61.75 -55.5,-60.75 -55.5,-60.75 -55.75,-58 -55.75,-58 -54.78754,-58.01415 -54.79037,-58.04041 -54.79175,-58.07026 -54.79002,-58.09055 -54.78382,-58.10906 -54.77485,-58.12457 -54.76518,-58.14308 -54.75759,-58.17471 -54.75034,-58.20575 -54.74309,-58.22485 -54.73653,-58.24216 -54.72893,-58.25768 -54.71995,-58.26902 -54.70889,-58.272 -54.69541,-58.26663 -54.68192,-58.26126 -54.66809,-58.26544 -54.65459,-58.27976 -54.64317,-58.29767 -54.63451,-58.31916 -54.62863,-58.34243 -54.62412,-58.37108 -54.6217,-58.39794 -54.62343,-58.42361 -54.62828,-58.44987 -54.63451,-58.47434 -54.64178,-58.49822 -54.64801,-58.56626 -54.66393,-58.60506 -54.67777,-58.64207 -54.69264,-58.68027 -54.70509,-58.72205 -54.71373,-58.76622 -54.7196,-58.80919 -54.72306,-58.87903 -54.72478,-58.94826 -54.72167,-59.0169 -54.7158,-59.08495 -54.71096,-59.15717 -54.70612,-59.16612 -54.70612,-59.23775 -54.70059,-59.24551 -54.70059,-59.29385 -54.69679,-59.3434 -54.69437,-59.36429 -54.69402,-59.38577 -54.69195,-59.40726 -54.69195,-59.42755 -54.69402,-59.44665 -54.70059,-59.46217 -54.71096,-59.46814 -54.72306,-59.47351 -54.73549,-59.48306 -54.74723,-59.4956 -54.75793,-59.50754 -54.76898,-59.52186 -54.7783,-59.54156 -54.7852,-59.56782 -54.79002,-59.5917 -54.79037,-59.61676 -54.78658,-59.62333 -54.78451,-59.66929 -54.77174,-59.71585 -54.76173,-59.7636 -54.75483,-59.81135 -54.74999,-59.86029 -54.74758,-59.90923 -54.74758,-59.95877 -54.7493,-60.00891 -54.7531,-60.06382 -54.75414,-60.11814 -54.75655,-60.17126 -54.76035,-60.22379 -54.76622,-60.27572 -54.77381,-60.32645 -54.78347,-60.37599 -54.7952,-60.42493 -54.80899,-60.47269 -54.82519,-60.48104 -54.82829,-60.50969 -54.83277,-60.54192 -54.83243,-60.56878 -54.82691,-60.59385 -54.81899,-60.61474 -54.80796,-60.63504 -54.79623,-60.65772 -54.78451,-60.68099 -54.77588,-60.74904 -54.75483,-60.75262 -54.75379,-60.7944 -54.74136,-60.86603 -54.72029,-60.9102 -54.7082,-60.98182 -54.68884,-61.02599 -54.67673,-61.07434 -54.66186,-61.12626 -54.64871,-61.17998 -54.64352,-61.2337 -54.64352,-61.28742 -54.64559,-61.34054 -54.64352)))",
 "EventDate is less than or equal to 2021-03-25"
 ]
}

 The dataset includes 1828 records from 40 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0231383-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mmoi1f
title: Occurrence Download

description: A dataset containing 25221 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Fratercula cirrhata (Pallas, 1769)"
 ]
}

 The dataset includes 25221 records from 115 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012337-180508205500799/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.yemtx6
title: Occurrence Download

description: A dataset containing 15 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Pomacanthus maculosus (Forsskål, 1775)",
 "HasGeospatialIssue is true",
 "HasCoordinate is true"
 ]
}

 The dataset includes 15 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014502-210819072339941/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.q6f3v6
title: Occurrence Download

description: A dataset containing 2751 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Tremarctos ornatus (F.G.Cuvier, 1825)"
 ]
}

 The dataset includes 2751 records from 68 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0034135-200221144449610/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.d37gnb
title: Occurrence Download

description: A dataset containing 109075 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Yorkshire Wildlife Trust - Non-sensitive records from all taxonomic groups"
 ]
}

 The dataset includes 109075 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0231391-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.brjmd1
title: Occurrence Download

description: A dataset containing 66842 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "BasisOfRecord is Observation",
 "BasisOfRecord is Human Observation",
 "BasisOfRecord is Specimen"
 ]
 },
 "TaxonKey is Portulaca L."
 ]
}

 The dataset includes 66842 records from 591 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012337-181003121212138/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bqh3c6
title: Occurrence Download

description: A dataset containing 3333 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "DatasetKey is iNaturalist Research-grade Observations",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Mergus serrator Linnaeus, 1758",
 "Year 2011-2018"
 ]
}

 The dataset includes 3333 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0237606-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8wkwa6
title: Occurrence Download

description: A dataset containing 404 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "TaxonKey is Tantilla melanocephala (Linnaeus, 1758)",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 404 records from 44 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0062476-200221144449610/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7e5t9c
title: Occurrence Download

description: A dataset containing 64 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Centruroides balsasensis Ponce & Francke, 2004"
 ]
}

 The dataset includes 64 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0240442-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fuc8mz
title: Occurrence Download

description: A dataset containing 873 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Country is Mexico",
 "TaxonKey is Amanita Pers."
 ]
}

 The dataset includes 873 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012338-181108115102211/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8tbnz8
title: Occurrence Download

description: A dataset containing 67 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Nymphaea glandulifera Rodschied ex G.Mey."
 ]
}

 The dataset includes 67 records from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0225940-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xyymfg
title: Occurrence Download

description: A dataset containing 5411 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-128.6 41.1,-119.3 41.1,-119.3 46.2,-128.6 46.2,-128.6 41.1))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 {
 "or" : [
 "Issue is Zero coordinate",
 "Issue is Coordinate out of range",
 "Issue is Geodetic datum invalid",
 "Issue is Geodetic datum assumed WGS84",
 "Issue is Coordinate reprojected",
 "Issue is Coordinate reprojection failed",
 "Issue is Coordinate reprojection suspicious",
 "Issue is Coordinate accuracy invalid",
 "Issue is Coordinate precision invalid",
 "Issue is Coordinate uncertainty meters invalid",
 "Issue is Coordinate precision/uncertainty mismatch",
 "Issue is Country coordinate mismatch",
 "Issue is Country mismatch",
 "Issue is Country invalid",
 "Issue is Country derived from coordinates",
 "Issue is Continent country mismatch",
 "Issue is Continent invalid",
 "Issue is Continent derived from coordinates",
 "Issue is Presumed swapped coordinate",
 "Issue is Presumed negated longitude",
 "Issue is Presumed negated latitude",
 "Issue is Recorded date mismatch",
 "Issue is Recorded date invalid",
 "Issue is Recorded date unlikely",
 "Issue is Taxon match fuzzy",
 "Issue is Taxon match higher rank",
 "Issue is Taxon match none",
 "Issue is Depth not metric",
 "Issue is Depth unlikely",
 "Issue is Depth min max swapped",
 "Issue is Depth non numeric",
 "Issue is Elevation unlikely",
 "Issue is Elevation min max swapped",
 "Issue is Elevation not metric",
 "Issue is Elevation non numeric",
 "Issue is Modified date invalid",
 "Issue is Modified date unlikely",
 "Issue is Identified date unlikely",
 "Issue is Identified date invalid",
 "Issue is Basis of record invalid",
 "Issue is Type status invalid",
 "Issue is Multimedia date invalid",
 "Issue is Multimedia URI invalid",
 "Issue is References URI invalid",
 "Issue is Error during interpretation",
 "Issue is Individual count invalid",
 "Issue is Individual count conflicts with occurrence status",
 "Issue is Occurrence status unparsable",
 "Issue is Occurrence status inferred from individual count",
 "Issue is ccurrence status inferred from basis of record",
 "Issue is Georeferenced date unlikely",
 "Issue is Georeferenced date invalid",
 "Issue is Ambiguous institution",
 "Issue is Ambiguous collection",
 "Issue is Institution match none",
 "Issue is Collection match none",
 "Issue is Institution match fuzzy",
 "Issue is Collection match fuzzy",
 "Issue is Institution collection mismatch",
 "Issue is Possibly on loan",
 "Issue is Different owner institution"
 ]
 },
 "OccurrenceStatus is Present",
 "TaxonKey is Carnivora",
 "Year is greater than or equal to 1900"
 ]
}

 The dataset includes 5411 records from 66 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0272130-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xzcarg
title: Occurrence Download

description: A dataset containing 29374837 species occurrences available in GBIF matching the query:
(Query is too complex. Can be viewed on the landing page)

 The dataset includes 29374837 records from 5353 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014882-210819072339941/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17466721
title: RFT — Toy Harmonic Demonstrator (Colab): QΩ Stability & Pre-emptive Trigger Record

description: This record documents a simplified, non-proprietary demonstration of harmonic self-stabilisation within the Rendered Frame Theory (RFT) framework.

Synthetic data are used to visualise mean-field QΩ behaviour and ζ_sync variance triggers under noise and periodic shocks.

Results show anticipatory correction and sustained coherence across simulated domains (Starship, Starlink, RHES, Neural).

All files are timestamped and sealed with SHA-512 verification.

This Zenodo record documents and preserves the RFT-Ω Harmonic Validation Interface (v3) — a live, interactive demonstrator of the Rendered Frame Theory (RFT) kernel hosted on Hugging Face Spaces.

 

The interface simulates harmonic stability (QΩ) and synchronisation coherence (ζ_sync) across multiple domains, each subject to controlled synthetic noise.

It serves as an open test harness for anticipatory stability, drift prediction, and noise resilience within the RFT-Ω kernel.

 

Key Features

 



Interactive profiles: AI/Neural, SpaceX/Aerospace, Energy/RHES, and Extreme Perturbation.

Adjustable synthetic noise (σ): Users can vary noise from 0.00–0.30 to test resilience.

Adaptive baselines: A light “memory” mechanism allows gradual self-stabilisation across runs.

Domain-specific weighting: Each profile balances QΩ vs ζ_sync based on operational priorities.

Range validation: Values are bounded (≤ 0.99) to eliminate saturation artifacts.


 

 

Purpose

This live kernel bridges theoretical RFT work with reproducible empirical validation, allowing external research and engineering teams (e.g., xAI, SpaceX, NASA, RobustBench, GLUE) to:

 



Benchmark RFT harmonic stability under controlled perturbations.

Analyse QΩ / ζ_sync variance as predictive drift signals.

Compare performance across domains and noise levels.

Validate low-variance behaviour and adaptive recovery.


 

 

Reference Implementation

Hugging Face Space: https://rftsystems-rft-omega-api.hf.space

Typical outputs:

{"System":"AI / Neural","Noise Scale":0.05,"QΩ":0.922,"ζ_sync":0.798,"status":"perturbed"}

 

For collaboration or validation requests, contact: Liam Grinstead — Liamgrinstead2@gmail.com

 

© 2025 Liam Grinstead | All Rights Reserved under RFT-IPURL v1.0, the Berne Convention (Paris Act 1971), and the UK Copyright, Designs and Patents Act 1988.
DOI: 10.5281/zenodo.17466722
title: RFT — Toy Harmonic Demonstrator (Colab): QΩ Stability & Pre-emptive Trigger Record

description: This record documents a simplified, non-proprietary demonstration of harmonic self-stabilisation within the Rendered Frame Theory (RFT) framework.

Synthetic data are used to visualise mean-field QΩ behaviour and ζ_sync variance triggers under noise and periodic shocks.

Results show anticipatory correction and sustained coherence across simulated domains (Starship, Starlink, RHES, Neural).

All files are timestamped and sealed with SHA-512 verification.

This Zenodo record documents and preserves the RFT-Ω Harmonic Validation Interface (v3) — a live, interactive demonstrator of the Rendered Frame Theory (RFT) kernel hosted on Hugging Face Spaces.

 

The interface simulates harmonic stability (QΩ) and synchronisation coherence (ζ_sync) across multiple domains, each subject to controlled synthetic noise.

It serves as an open test harness for anticipatory stability, drift prediction, and noise resilience within the RFT-Ω kernel.

 

Key Features

 



Interactive profiles: AI/Neural, SpaceX/Aerospace, Energy/RHES, and Extreme Perturbation.

Adjustable synthetic noise (σ): Users can vary noise from 0.00–0.30 to test resilience.

Adaptive baselines: A light “memory” mechanism allows gradual self-stabilisation across runs.

Domain-specific weighting: Each profile balances QΩ vs ζ_sync based on operational priorities.

Range validation: Values are bounded (≤ 0.99) to eliminate saturation artifacts.


 

 

Purpose

This live kernel bridges theoretical RFT work with reproducible empirical validation, allowing external research and engineering teams (e.g., xAI, SpaceX, NASA, RobustBench, GLUE) to:

 



Benchmark RFT harmonic stability under controlled perturbations.

Analyse QΩ / ζ_sync variance as predictive drift signals.

Compare performance across domains and noise levels.

Validate low-variance behaviour and adaptive recovery.


 

 

Reference Implementation

Hugging Face Space: https://rftsystems-rft-omega-api.hf.space

Typical outputs:

{"System":"AI / Neural","Noise Scale":0.05,"QΩ":0.922,"ζ_sync":0.798,"status":"perturbed"}

 

For collaboration or validation requests, contact: Liam Grinstead — Liamgrinstead2@gmail.com

 

© 2025 Liam Grinstead | All Rights Reserved under RFT-IPURL v1.0, the Berne Convention (Paris Act 1971), and the UK Copyright, Designs and Patents Act 1988.
DOI: 10.15468/dl.n8dbkx
title: Occurrence Download

description: A dataset containing 70 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-9.15213 38.51668,-9.13618 38.51668,-9.13618 38.52972,-9.15213 38.52972,-9.15213 38.51668))",
 "TaxonKey is Testudines"
 ]
}

 The dataset includes 70 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006596-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.j7y8uh
title: Occurrence Download

description: A dataset containing 140597 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Aedes albopictus"
 ]
}

 The dataset includes 140597 records from 216 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006550-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.gqswnu
title: Occurrence Download

description: A dataset containing 28 records in GBIF matching the query:
SELECT
 kingdom,
 kingdomkey,
 phylum,
 phylumkey,
 class,
 classkey,
 "order",
 orderkey,
 family,
 familykey,
 genus,
 genuskey,
 species,
 specieskey,
 PRINTF('%04d-%02d', "year", "month") yearmonth,
 GBIF_EEARGCODE(1000, decimallatitude, decimallongitude, COALESCE(coordinateuncertaintyinmeters, 1000)) eeacellcode,
 IF(ISNULL(genuskey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY genuskey, GBIF_EEARGCODE(1000, decimallatitude, decimallongitude, COALESCE(coordinateuncertaintyinmeters, 1000)), PRINTF('%04d-%02d', "year", "month"))) genuscount,
 COUNT(*) occurrences,
 MIN(GBIF_TEMPORALUNCERTAINTY(eventdate, eventtime)) mintemporaluncertainty,
 MIN(COALESCE(coordinateuncertaintyinmeters, 1000)) mincoordinateuncertaintyinmeters
FROM
 occurrence
WHERE
 occurrence.basisofrecord = 'PRESERVED_SPECIMEN'
 AND occurrence.countrycode = 'DE'
 AND (CAST(occurrence.taxonkey AS INTEGER) = 5392633 OR CAST(occurrence.acceptedtaxonkey AS INTEGER) = 5392633 OR CAST(occurrence.kingdomkey AS INTEGER) = 5392633 OR CAST(occurrence.phylumkey AS INTEGER) = 5392633 OR CAST(occurrence.classkey AS INTEGER) = 5392633 OR CAST(occurrence.orderkey AS INTEGER) = 5392633 OR CAST(occurrence.familykey AS INTEGER) = 5392633 OR CAST(occurrence.genuskey AS INTEGER) = 5392633 OR CAST(occurrence.specieskey AS INTEGER) = 5392633)
 AND occurrence.hasgeospatialissues = FALSE
 AND NOT GBIF_STRINGARRAYCONTAINS(occurrence.issue, 'TAXON_MATCH_FUZZY', TRUE)
 AND (occurrence.distancefromcentroidinmeters &gt;= 2000.0 OR occurrence.distancefromcentroidinmeters IS NULL)
 AND occurrence.occurrencestatus = 'PRESENT'
 AND (occurrence.specieskey IS NOT NULL AND occurrence."year" IS NOT NULL AND occurrence."month" IS NOT NULL AND occurrence.hascoordinate = TRUE)
GROUP BY
 occurrence.kingdom,
 occurrence.kingdomkey,
 occurrence.phylum,
 occurrence.phylumkey,
 occurrence.class,
 occurrence.classkey,
 occurrence."order",
 occurrence.orderkey,
 occurrence.family,
 occurrence.familykey,
 occurrence.genus,
 occurrence.genuskey,
 occurrence.species,
 occurrence.specieskey,
 PRINTF('%04d-%02d', "year", "month"),
 GBIF_EEARGCODE(1000, decimallatitude, decimallongitude, COALESCE(coordinateuncertaintyinmeters, 1000))

 The dataset's 28 records were derived from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006588-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.21334/npolar.2020.a59e0486
title: Conflux ship-based CTD data 2011
DOI: 10.15468/dl.t8gdzr
title: Occurrence Download

description: A dataset containing 6142496 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Europe",
 "Country is one of (Ukraine, Belarus, Moldova, Republic of, Latvia, Lithuania, Estonia)",
 "OccurrenceStatus is Present",
 "TaxonKey is Chordata",
 "Year 1970-2025"
 ]
}

 The dataset includes 6142496 records from 417 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006577-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17476037
title: Exploring Data-driven Real Estate Price Prediction in a Developing Country: The Case of Pakistan

description: The price prediction is critical for making better decisions when buying or selling a real estate. Currently, there is a lack of data-driven price prediction studies on Pakistani real estate market, which publicly share their datasets and the sources of data collection. In addition, mobile and webapplications of Pakistani electronic markets are also missing the data-driven real estate price prediction. This study collected data of 50 thousand real estate properties of Lahore between 2020 and 2024. The data collected from oldest and most used mobile and web-application. The regression-based machine learning (ML) and deep learning (DL) models are trained on original values of dataset and transformed values (using log and z-score) and subsets of the dataset. The ensemble ML model (i.e., Extra Trees) trained on a subset of features that are selected using mutual information performed the best with evaluation measures of R2 = 0.96, RMSE = 0.09, MAE = 0.05, and MAPE =0.008. The DL model (i.e., Bi-LSTM) trained on logged transformed complete dataset achieved best results based on evaluation measures i.e. R2 = 0.89, RMSE = 0.14, MAE=0.09, MAPE=0.01. The log transformation of feature values helped to achieve best performances of both ML and DL models.
DOI: 10.5281/zenodo.17476038
title: Exploring Data-driven Real Estate Price Prediction in a Developing Country: The Case of Pakistan

description: The price prediction is critical for making better decisions when buying or selling a real estate. Currently, there is a lack of data-driven price prediction studies on Pakistani real estate market, which publicly share their datasets and the sources of data collection. In addition, mobile and webapplications of Pakistani electronic markets are also missing the data-driven real estate price prediction. This study collected data of 50 thousand real estate properties of Lahore between 2020 and 2024. The data collected from oldest and most used mobile and web-application. The regression-based machine learning (ML) and deep learning (DL) models are trained on original values of dataset and transformed values (using log and z-score) and subsets of the dataset. The ensemble ML model (i.e., Extra Trees) trained on a subset of features that are selected using mutual information performed the best with evaluation measures of R2 = 0.96, RMSE = 0.09, MAE = 0.05, and MAPE =0.008. The DL model (i.e., Bi-LSTM) trained on logged transformed complete dataset achieved best results based on evaluation measures i.e. R2 = 0.89, RMSE = 0.14, MAE=0.09, MAPE=0.01. The log transformation of feature values helped to achieve best performances of both ML and DL models.