Freelancers using Streamlit

Freelancers using StreamlitFreelancers using Streamlit

Projects People

proLahore, Pakistan

AI Integration & Automation Engineer | Full-Stack Web Apps

$50k+: Earned

63x: Hired

4.9: Rating

90: Followers

Expert

Expert

+2

AI Integration & Automation Engineer | Full-Stack Web Apps

Cover image for Autonomous Multi-Agent Market Research System Development

Autonomous Multi-Agent Market Research System Development

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Cover image for Magnai | UK Public Affairs

Magnai | UK Public Affairs

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Cover image for Humoni - secure housing in under 72 hours

Humoni - secure housing in under 72 hours

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Cover image for Wellbeing Wizard AI

Wellbeing Wizard AI

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Istiak Ahmed Khan

Dhaka, Bangladesh

Power BI Data Analyst + ML AI Automation Expert

5.0: Rating

84: Followers

Power BI Data Analyst + ML AI Automation Expert

Cover image for Education Program Analytics Dashboard –

Education Program Analytics Dashboard – Data Analytics Solution Handling large-scale program data without clear visibility can make impact measurement difficult. This dashboard is designed to give organizations a complete, real-time view of program performance, reach, and funding — all in one place. What You Get : A powerful, interactive dashboard that helps track beneficiaries, program outputs, regional performance, and donor contributions with clarity and precision. Key Capabilities: Monitor total beneficiaries and gender distribution Track program reach across provinces and sectors Analyze quarterly trends and growth patterns Evaluate donor funding allocation and impact Identify top-performing program categories and outputs Explore education level distribution and engagement For NGOs and large programs, data is critical for decision-making and reporting. This dashboard helps you measure impact, improve transparency, and optimize resource allocation — making your data meaningful and actionable. Perfect For : NGOs and non-profit organizations Government programs International development agencies Research and policy teams If you want a professional, insight-driven dashboard that clearly communicates impact and performance, I can create a customized solution tailored to your organization.

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Cover image for Predictive Marketing Analytics: Optimizing Advertising

Predictive Marketing Analytics: Optimizing Advertising ROI 1. The Business Problem Companies often struggle to determine which marketing channels actually drive revenue. Without a data-driven approach, advertising budgets are often misallocated across platforms like TV, Radio, and Newspapers, leading to inefficient spending and missed sales targets. This project aimed to build a predictive model to quantify the relationship between multi-channel marketing spend and total sales. 2. Strategic Insights & Market Analysis Through a rigorous analysis of historical advertising data, I identified the specific drivers of revenue growth: Dominant Revenue Driver: TV advertising emerged as the most critical factor, showing a massive 0.9 correlation with sales. Efficiency Analysis: While Radio and Newspaper spending contributed to the marketing mix, their direct impact on sales was significantly lower (0.35 and 0.16 correlation, respectively), suggesting a need for budget reallocation. Predictive Power: My analysis revealed that 81.6% of the variance in sales can be explained by TV advertising spend alone, providing a highly reliable foundation for future budget forecasting. 3. Data-Driven Solution I developed a Linear Regression model to provide leadership with a mathematical framework for sales forecasting. Reliability: The model was validated using a 70/30 train-test split, ensuring it performs accurately on new, unseen market data. Accuracy: The system achieved a strong R-squared value of 0.79 on the test set, meaning it can accurately predict nearly 80% of sales fluctuations based on planned marketing spend. Error Management: I performed a detailed residual analysis to confirm that the model’s error terms were normally distributed, ensuring the reliability of the forecasted figures. 4. Business Impact Budget Optimization: Provided a clear mathematical equation (Sales=6.948+0.054×TV) that allows the marketing team to calculate the expected return on every dollar spent on TV advertising. Strategic Planning: Enabled the transition from "gut-feeling" marketing to precision budgeting, allowing the company to maximize ROI by prioritizing high-impact channels. Risk Mitigation: By identifying the variance that the model couldn't explain, I helped the business identify where external market factors might still influence sales, allowing for more conservative and realistic financial planning. Technical Stack Modeling: Simple Linear Regression, Statsmodels (OLS), Scikit-learn. Analytics: Python, Pandas, NumPy. Visualization: Seaborn, Matplotlib, 3D Scatter Plots

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Cover image for End-to-End Machine Learning Pipeline for

End-to-End Machine Learning Pipeline for Telecom Customer Churn 1. The Business Problem Customer churn is a major challenge for telecommunications companies, driven by competition, service issues, and changing consumer preferences. This project was designed to transition the company from reactive support to proactive retention using data-driven strategies such as customer segmentation, personalized offers, and loyalty programs,. 2. Data Exploration & Insights (EDA) I performed a comprehensive descriptive analysis on a database of 7,043 customers with 21 distinct variables,. Key findings included: Contractual Risk: Customers on month-to-month contracts showed significantly higher churn compared to those on one- or two-year commitments,. Service Preference: While Fiber Optic plans were the most popular, they also represented a critical segment for monitoring due to their higher price points,. Financial Indicators: Churned customers had a higher average monthly charge of $74.44, compared to $61.27 for retained customers. Payment Behavior: The "Electronic Check" payment method was most strongly associated with service cancellation,. 3. Engineering & Preprocessing Pipeline To prepare the data for high-performance modeling, I implemented a rigorous preprocessing workflow: Data Cleaning: Removed irrelevant identifiers like customerID and addressed potential data quality issues. The dataset was verified to have zero missing or NaN values,. Feature Engineering: Applied Label Encoding to transform categorical text variables into a numerical format suitable for machine learning algorithms,. Data Splitting: Adopted a standard 80/20 train-test split to ensure the model could generalize effectively to unseen data,. 4. Model Development & Benchmarking I developed and benchmarked eight distinct machine learning algorithms to identify the most effective solution for this specific application: Linear & Probabilistic: Logistic Regression, Naive Bayes. Tree-Based: Decision Tree, Random Forest. Boosting Frameworks: AdaBoost, Gradient Boosting, XGBoost, and LightGBM,. 5. Performance Evaluation & Results Models were evaluated using ROC curves, confusion matrices, and detailed classification reports,. Winner: Logistic Regression achieved the highest accuracy at 81.83%,. Secondary Performers: Gradient Boosting (81.05%) and AdaBoost (80.98%) also showed strong predictive power. 6. Technical Conclusion This data-driven approach proves that proactive churn prediction is essential for business sustainability. By identifying that customers prioritize high-speed fiber optic services but are sensitive to pricing and contract terms, the company can now optimize its pricing and retention strategies to maximize user satisfaction and revenue.

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Cover image for 3D Molecular Intelligence: Accelerating Drug

3D Molecular Intelligence: Accelerating Drug Discovery through Predictive Analytics The Impact: This project addresses a critical bottleneck in pharmaceutical research: determining molecular solubility (logS). By replacing slow, expensive lab tests with high-precision machine learning, this system enables scientists to screen thousands of compounds in seconds, significantly reducing the cost and time required to bring new life-saving drugs to market. Drastic Cost Reduction: The predictive pipeline reduces early-stage experimental screening costs by 70–90%, allowing research teams to focus resources on the most promising drug candidates. High-Precision Forecasting: Utilizing a hybrid 3D feature engineering approach, the system achieves a remarkable 91.3% accuracy (R² score) in predicting solubility, providing a highly reliable alternative to physical testing. Accelerated R&D Cycles: By automating the identification of viable molecules, the tool dramatically shortens the "hit-to-lead" time in pharma and materials science, getting products to market faster. Empowering Researchers: I deployed a professional Streamlit dashboard featuring an interactive 3D molecular viewer. This allows non-technical chemists to visualize complex structures and make data-driven decisions without needing to write a single line of code

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Emmanuel Ezeokeke

AI Expert |AI Agent| AI RAG | LangChain | LangGraph | CrewAI

AI Expert |AI Agent| AI RAG | LangChain | LangGraph | CrewAI

Cover image for All My Reviews on Upwork

All My Reviews on Upwork

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Cover image for Local AI Agent Troubleshooter

Local AI Agent Troubleshooter

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Cover image for AI System for Doctor Appointment Management

AI System for Doctor Appointment Management

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Cover image for I made a tutorial for an AI agent where I built an AI-powere...

I made a tutorial for an AI agent where I built an AI-powered blockchain analytics platform (https://www.youtube.com/watch?v=ceRZWLkxEbU) built with CrewAI that analyzes crypto wallets across Ethereum, Polygon, BSC, Arbitrum, and Base. Uses 4 specialized agents - Portfolio Analyst, Transaction Specialist, Investment Strategist, and Intelligence Synthesizer - working sequentially to process on-chain data via Zapper API. Delivers good reports with portfolio composition, risk assessment, behavioral patterns, and investment recommendations through CLI and Streamlit interfaces with real-time tracking and downloadable outputs. Try it out: https://onchain-ai-agent.onrender.com/ Github code: https://github.com/Emarhnuel/Onchain-AI-agent

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Amsterdam, Netherlands

Marketing Data Specialist bridging marketing & data science

Marketing Data Specialist bridging marketing & data science

Cover image for Apple Sales Dashboard

Apple Sales Dashboard

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Cover image for Global Tourism Interactive Dashboard

Global Tourism Interactive Dashboard

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Cover image for WeWorkRemotely Remote Jobs Dashboard

WeWorkRemotely Remote Jobs Dashboard

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Cover image for Global Energy Transition Dashboard

Global Energy Transition Dashboard

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Freelance Data Scientist | Python & ML Expert

10: Followers

Freelance Data Scientist | Python & ML Expert

Cover image for Fraud Transaction Detection System

Fraud Transaction Detection System

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Cover image for Hybrid AI Movie Recommendation System for Pre-2015 Films

Hybrid AI Movie Recommendation System for Pre-2015 Films

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Cover image for Lung Cancer Survival Prediction Model Development

Lung Cancer Survival Prediction Model Development

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Full StackDev | MVP Builder for SAAS | AI Agents

$10k+: Earned

5x: Hired

5.0: Rating

47: Followers

Full StackDev | MVP Builder for SAAS | AI Agents

Cover image for Dynamic Customer Churn Prediction Engine

Dynamic Customer Churn Prediction Engine

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2

Cover image for Innovative Emu Website Concept: Capture Your Audience Today

Emu - Website Concept.

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Cover image for Exploring how softness, motion, and

Exploring how softness, motion, and a hint of digital texture can live together. Curious what direction resonates most.

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Cover image for Landing page for an ai

Landing page for an ai company.

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5

195

Senior FullStack & AI Engineer | Product-Driven Solutions

$25k+: Earned

5x: Hired

5.0: Rating

16: Followers

Senior FullStack & AI Engineer | Product-Driven Solutions

Cover image for Regulated Builds

Regulated Builds

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3

Cover image for Development of Daemora Autonomous AI Agent

Development of Daemora Autonomous AI Agent

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Cover image for AutoGlow Premium Car Detailing Website Design

AutoGlow Premium Car Detailing Website Design

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1

Cover image for Choose the Perfect Thumbnail for My Contra Project

Help me choose a thumbnail for my Contra project 👇 Two directions: 👉 Clean & simple 👉 Bold & eye-catching Which one would you click first? Left or Right? (first instinct 👀) Can share Figma if anyone wants 👀

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269

proTunis, Tunisia

Multimedia Imaging Producer| AI Creative | Media Workflows

3x: Hired

5.0: Rating

50: Followers

Multimedia Imaging Producer| AI Creative | Media Workflows

Cover image for Radio Imaging Audio Generator Development

Radio Imaging Audio Generator Development

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5

Cover image for The web is no longer

The web is no longer just for playing audio. It's an engine. 🏎️💨 I took a complex game-audio soundscape (a Ferrari 458 GT3 V8) and rebuilt the entire architecture natively in the browser. No Unity. No Unreal. Just pure code. Here is a screen recording of the system in action. Notice how the crossfaded voice layers and gear shift triggers react instantly to the drive parameters. Turn your sound on 🔊 and check out the real-time UI. Let me know your thoughts in the comments! 👇

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Cover image for 🚀 GrabClip v3.0 is officially

🚀 GrabClip v3.0 is officially live! We haven't stopped building. We just completely redesigned the batch downloading experience to make grabbing your media faster, smarter, and more automated. Whether you need to download a massive 4+ hour video, pull an entire educational "Learning Path" playlist, or grab multiple links from over 1000+ different websites (YouTube, TikTok, Instagram, X, etc.) at the same time—GrabClip v3.0 handles it effortlessly. ✨ What’s new in v3.0? ⚡ Completely Redesigned Batch Queue: The batch system has been rebuilt from the ground up into a clean, dedicated popup window. Paste your URLs, and GrabClip instantly auto-detects the platform for each one. Pick your format (4K, 1080p, MP3, FLAC), hit "Download All", and track everything with real-time progress bars for individual items and the overall batch. 🚀 Speed Boost Built-In: No more digging through settings. The 1x to 8x Speed Boost slider is now built directly into the batch dialog! Crank it up to 8x, hit download, and watch heavy 4K files and long learning paths fly through. 🤖 Smarter Madame AI Automation: Our smart assistant is now deeply wired into your workflow. Just copy multiple URLs to your clipboard, and the batch dialog opens automatically. Madame AI tracks the progress and notifies you at every single stage—from analysis to download completion. 📚 Ultimate Stability & Smarter History: Everything you loved from v2.0 is still here and improved. Enjoy a smarter download history with custom sorting, zero duplicates, a new stats bar, and crucial bug fixes for an incredibly smooth experience. ━━━━━━━━━━━━━━━━━━ 🔑 As always, GrabClip is 100% FREE. Get your License Key and download the v3.0 update here: 👉 grabclip.bilsimaging.com (http://grabclip.bilsimaging.com) ━━━━━━━━━━━━━━━━━━ We automate. We build. We create. — Bilsimaging, Tunisia 🇹🇳

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Cover image for 🚀 Just Released: AI Voice Cloning Workflow I'm excited to s...

🚀 Just Released: AI Voice Cloning Workflow I'm excited to share my latest ComfyUI workflow - Bilsimaging Voice Cloning with Qwen3 TTS! 🎯 What it does: Clone any voice with just a 10-40 second audio sample and generate speech in multiple languages. ✨ Key Features: • One-click voice cloning • Auto transcription with Whisper AI Try it free on RunningHub: 👉 https://www.runninghub.ai/post/2015450678159745025/?inviteCode=e1ajqoho #AI #VoiceCloning #TTS #ComfyUI #ContentCreation #Innovation

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