Freelance Data Modelling Analysts in Islamabad
Freelance Data Modelling Analysts in Islamabad
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Ali Hassan
Rawalpindi, Pakistan
Transforming Data into Actionable Insights 🔍
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Transforming Data into Actionable Insights 🔍
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SALES PREDICTION USING PYTHON
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236
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IRIS FLOWER CLASSIFICATION
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127
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Titanic Analysis Project
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60
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Bikes Sales Analysis
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248
Data Modelling Analyst
(3)
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Hammad Tariq
Islamabad, Pakistan
Data Warehouse Engineer | Cloud Enthusiast | Data Engineer
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Data Warehouse Engineer | Cloud Enthusiast | Data Engineer
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Google Data Pipeline
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36
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Dashboard Migration
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39
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ETL Processing On Google Cloud Using Dataflow and Big Query
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41
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Data Modelling Analyst
(3)
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Haider khan
Islamabad, Pakistan
Software engineer skilled in data analysis, machin
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Software engineer skilled in data analysis, machin
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Child Labor Risk Analysis
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7
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Predictive Analysis for Hotel Booking Cancellations
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7
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Car Condition Prediction
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5
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Data Modelling Analyst
(3)
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Mohammad Roshaan Butt
Rawalpindi, Pakistan
Data Engineer | Data Scientist
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Data Engineer | Data Scientist
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streaming pipeline and data warehousing with stock market data
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6
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Automated batch processing for POS transactions
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4
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E Commerce Analytics Pipeline
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6
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Data Modelling Analyst
(1)
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Sareer Ahmad
Rawalpindi, Pakistan
Cheminformatics & ML Specialist | Python, RDKit & XGBoost
New to Contra
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Cheminformatics & ML Specialist | Python, RDKit & XGBoost
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TSCA Compliance Navigator
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0
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GHS Chemical Hazard Classification (Interpretable ML)
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0
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Tox21 Toxicity Screener
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1
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Olist E-Commerce Analytics Dashboard
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1
Data Modelling Analyst
(2)
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Khalil Ahmad
Rawalpindi, Pakistan
Statistician, Biostatistician and Data Analyst
New to Contra
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Statistician, Biostatistician and Data Analyst
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Advanced Methodology for Forecasting the Key Health Indicators
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35
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IAbstract. Stem cell (SC) transplantation has shown potential as a therapeutic approach for premature ovarian failure (POF). Despite this, no quantitative analysis has been conducted on the efficacy of SC therapy for POF in humans. To address this gap, the present study conducted a meta-analysis to evaluate the effectiveness of the transplantation of SC in improving ovarian function among POF patients. A systematic review in this regard by searching PubMed, ScienceDirect, clinicalTrial.gov (http://clinicalTrial.gov), and Cochrane's library databases was conducted to identify relevant studies, while associated reviews were also considered. The extracted data included parameters such as estradiol (E2), follicle-stimulating hormone (FSH), follicle count (FC), ovarian weight (OW), number of pregnancies, and live birth. As per the combined effect taking the last follow-up time, the level of FSH and AMH for the SC group was lower than these were at the baseline as (SMD: 1.58, 95% CI: 0.76 to 3.92, P-value: 0.185 > 0.05, I2 : 94.03%) and (SMD: 1.34, 95% CI: 0.77 to 1.92, P-value: 0.001 < 0.05, I2 : 0%) respectively. While the means of E2 and OW for the SC group was higher than these were at the baseline as (SMD: 0.47, 95% CI: 0.73 to 0.21, P-value: 0.001 < 0.01, I2 : 38.23%) and (SMD: 1.18, 95% CI: 2.62 to 0.26, P-value: 0.108 > 0.05, I2 : 76.68%) respectively. The overall effect size measured with proportion of pregnancy and live birth at a 5% level of significance expected SC transplantation results were as (combined proportion: 0.09, 95% CI: 0.03 to 0.15, P-value: 0.002 < 0.05, I2 : 46.29%) and (SMD: 0.09, 95% CI: 0.03 to 0.15, P-value: 0.003 < 0.05, I2 : 1.76%) respectively. Based on the fixed-effects model, the estimated average log odds ratio of Follicles count was 1.0234 (95% CI: 0.1252 to 1.9216). Therefore, the average outcome differed significantly from zero (Pvalue: 0.0255 < 0.05) due to SC transplantation. These results suggest that using SCs to restore ovarian function may be viable for treating POF. However, larger and better-quality investigations would need to be conducted in the future due to the heterogeneity of the examined studies.
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26
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Some of received recommendation from top professionals on LinkedIn.
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29
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Received Recommendations from different professional on LinkedIn after succcessfully completing their projects.
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50
Data Modelling Analyst
(1)
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Arbab Khan
Rawalpindi, Pakistan
Data Science | Reinforcement Learning | R&D
New to Contra
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Data Science | Reinforcement Learning | R&D
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Cleaning & Visualization of data using Python
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64
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Windows Forms based application with AI integration
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55
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How much time does it take for a Bitcoin transaction to be accepted?
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68
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Earthquake prediction using LSTM
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67
Data Modelling Analyst
(1)
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Sadaqat Ali
Islamabad, Pakistan
Where geography meets design excellence
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Where geography meets design excellence
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Geospatial Analyst & 3D Modeling Specialist for Infrastructure, Mining & Urban Development
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85
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Designed and developed an interactive web visualization application featuring dynamic maps, data dashboards, and user-friendly analytics. The platform enables efficient exploration of complex data through responsive and visually engaging interfaces.
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62
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Created a 3D urban parking facility model for a city development project, showcasing efficient parking layouts, traffic circulation, and public accessibility. The visualization supported urban planning, infrastructure design, and decision-making processes.
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72
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Developed a high-resolution 3D road corridor model using GIS and terrain data to visualize road alignment, elevation profiles, and surrounding landscapes. The project delivered realistic engineering-grade visualizations for planning, stakeholder presentations, and project documentation.
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75
Data Modelling Analyst
(1)
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