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Anurag Nagare's avatar
Anurag Nagare
Mumbai, India
I’m an AI & Machine Learning engineer with expertise in deve
I’m an AI & Machine Learning engineer with expertise in deve
Cover image for Everyone's talking about quantum computing.
Everyone's talking about quantum computing. Nobody's using it to feed farmers. India loses 20–30% of its crop yield every year to diseases and pests. Not because farmers don't care — but because early detection is hard, expensive, and inaccessible to the people who need it most. The existing solutions? Either a basic image classifier trained on lab-perfect photos that fail in real field conditions, or an agronomist visit that costs time and money most small farmers don't have. So I built QuantumEdge AgriGuard — a hybrid Quantum Neural Network app where a farmer can photograph a diseased leaf on their phone and get an instant diagnosis in under 5 seconds. Here's what makes it different from just another plant disease detector: Instead of a pure classical CNN, I built a hybrid architecture — a ResNet/EfficientNet backbone extracts visual features, then passes them into a Variational Quantum Circuit (VQC) for the final classification. The quantum layer uses angle embedding + StronglyEntanglingLayers, which gives it a measurable edge on small, noisy datasets — exactly the kind of data you get from Indian field conditions. The app doesn't just tell you what disease it is. It gives you: → Confidence score → Organic + chemical remedies (India-specific) → Yield impact estimate → A live classical vs quantum accuracy comparison so you can see the difference yourself I tested the quantum advantage claim honestly — ran both models on the same downsampled PlantVillage dataset and tracked accuracy, F1-score, and inference time side by side. The results are on the dashboard. No hand-waving. Built with PennyLane + PyTorch + Plotly Dash. Designed to run on simulators today and on QpiAI-Indus 25-qubit hardware tomorrow.
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Cover image for CricVision AI - Advanced Cricket Analytics Dashboard! CricVi...
CricVision AI - Advanced Cricket Analytics Dashboard! CricVision AI is an intelligent cricket analytics platform that leverages machine learning to provide real-time match predictions and comprehensive player insights. The dashboard predicts wicket probability, expected runs per ball, and boundary likelihood using three trained ML models with StandardScaler normalization. It features interactive match scenarios (Powerplay, Middle, and Death overs), over-by-over projections, win probability calculations, and economy rate forecasts. Users can compare players head-to-head, analyze form trends over recent innings, visualize run distribution through wagon wheels, and get AI confidence scores for all predictions - making it a complete solution for cricket enthusiasts and analysts.
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Cover image for I created WealthWise Agent, a smart personal finance planner...
I created WealthWise Agent, a smart personal finance planner designed to craft personalized budget plans and investment strategies. This app takes into account user inputs like salary, expenses, and financial goals, and then uses a Large Language Model (Gemini) to analyze these factors based on the 50/30/20 budgeting rule. It offers a clear step-by-step reasoning log, a detailed JSON-structured financial plan, and an interactive visualization of budget allocation, empowering users to make informed choices to reach their financial goals. 💻 Tech Stack Used: Frontend/UI: Gradio (custom themed with CSS, Orbitron font) AI/Logic: Google Gemini (gemini-1.5-flash) with LangChain agents Data: yFinance API for real-time stock/ETF data, Pandas & NumPy for calculations Visualization: Plotly Express for interactive charts
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Cover image for Everyone's building AR filters and
Everyone's building AR filters and calling it "computer vision magic." Almost nobody's asking what's actually happening underneath — that most of these effects are just clever masking, not detection. Here's proof. I built an invisibility cloak that runs entirely in the browser, no green screen, no chroma key, no model training. https://github.com/AnuragNagare/Ghost-frame
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Dash Plotly(3)
Mohsen M's avatar
Mohsen M
Italy
AI Chatbot Developer | Data Scientist | ML Engineer
AI Chatbot Developer | Data Scientist | ML Engineer
Cover image for Electricity Consumption Prediction for Malmi Office Building
Electricity Consumption Prediction for Malmi Office Building
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Cover image for Machine Learning for Bone Tumor Diagnostics
Machine Learning for Bone Tumor Diagnostics
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Cover image for Incident Response Fairness Analysis
Incident Response Fairness Analysis
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Istiak Ahmed Khan's avatar
Istiak Ahmed Khan
Dhaka, Bangladesh
Power BI Data Analyst + ML AI Automation Expert
5.0
Rating
106
Followers
Power BI Data Analyst + ML AI Automation Expert
Cover image for Saving Lives through Early Clinical
Saving Lives through Early Clinical Risk Detection Application is live at: https://495a-35-237-151-197.ngrok-free.app The Problem: Heart failure is a leading cause of global mortality; the difference between survival and fatality often depends on how early a high-risk patient is identified. The Solution: I developed a clinical diagnostic tool that analyzes patient health markers to forecast mortality risk, assisting medical professionals in prioritizing life-saving care. Key Impacts: Early Intervention: The model identified that follow-up time is the single most critical factor in reducing fatalities, emphasizing the need for early diagnosis and consistent monitoring. Precision Diagnostics: By analyzing heart efficiency (ejection fraction) and chemical markers like serum creatinine, the tool provides a high-accuracy (84.49%) risk score for every patient. Clinical Support: The system helps doctors look past "statistical flukes" by accounting for outliers in medical data, ensuring that extreme clinical cases are caught rather than ignored. Actionable Health Insights: Demonstrated a clear link between age, heart efficiency, and chemical abundance, giving providers a data-driven framework to improve long-term patient outcomes
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Cover image for The E-Commerce Orders Dashboard provides
The E-Commerce Orders Dashboard provides a comprehensive overview of order performance, revenue trends, and customer purchasing behavior. Designed for online businesses, this dashboard transforms transactional order data into actionable insights that support growth, operational efficiency, and strategic decision-making.
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Cover image for Email Marketing Analytics Dashboard –
Email Marketing Analytics Dashboard – UI/UX Design Struggling to track campaign performance across multiple channels? This dashboard is designed to give you a complete, real-time view of your marketing efforts in one clean and intuitive interface. A powerful, easy-to-use dashboard that helps you monitor email, SMS, social media, and push campaigns without the confusion of scattered data. Every key metric is presented clearly so you can make faster, smarter decisions. Key Capabilities: Track open rates, click rates, conversions, and revenue in real time, Compare performance across multiple marketing channels, Identify your top-performing campaigns instantly, Understand audience engagement with clear visual breakdowns, Spot trends and optimize campaigns quickly. Most businesses run campaigns but struggle to understand what’s actually working. This dashboard eliminates guesswork by turning your data into clear, actionable insights — helping you improve ROI and scale winning strategies. Perfect For: Digital marketers, E-commerce brands, Agencies managing multiple campaigns, Startups looking to optimize growth. If you want a high-converting, professional dashboard that not only looks great but drives real business decisions — I can help you build it.
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Cover image for Comprehensive Financial Performance Dashboard in Power BI
The Financial Performance Dashboard provides a comprehensive overview of an organization’s financial health by tracking revenue, expenses, profitability, and key financial indicators. Built using Power BI, this dashboard enables finance teams and decision-makers to monitor performance, identify trends, and make data-driven strategic decisions.
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Abu Aasif Ansari's avatar
Abu Aasif Ansari
Bhiwandi, India
I build AI-powered data apps and dashboards
12
Followers
I build AI-powered data apps and dashboards
Cover image for Smart Data Analyst — AI-Powered
Smart Data Analyst — AI-Powered Data Analysis App Built a fully working AI-powered data analysis app from scratch using Streamlit and Gemini API. The problem: Most business owners have data in Excel or CSV files but no easy way to analyze it without hiring a full-time analyst or learning Python. So I built a tool where you just upload your file — and the app does the rest. → Auto-detects KPIs from any dataset → Generates charts automatically → Ask questions in plain English — get instant answers with tables and charts → Downloads full PDF report with KPIs and charts → RAG memory — remembers past questions Tech: Streamlit · Gemini API · Python · Pandas · Plotly 🔗 Live: https://smart-data-analyst-ahkz32vjd6dzvhmexkrhdm.streamlit.app/ (https://smart-data-analyst-ahkz32vjd6dzvhmexkrhdm.streamlit.app/)⭐ GitHub: https://github.com/AbuAsifAnsari/smart-data-analyst (https://github.com/AbuAsifAnsari/smart-data-analyst)
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Cover image for Project Overview This is a personal portfolio and services s...
Project Overview This is a personal portfolio and services site built for a working freelancer — myself — as part of the Make It Real Challenge. I'm a data visualization specialist and AI dashboard developer, and I wanted the site itself to reflect that work rather than just describe it. So instead of stock photography and generic copy, every visual on the site is a real screenshot from a project I've actually shipped. The Concept Most freelance portfolio sites lean on polished lifestyle photography — laptops on wooden desks, people in blazers looking thoughtfully at monitors. I wanted to flip that: let the actual product screens do the talking. The site is built around a simple idea — "solutions built on data, not guesswork" — and that shows up literally in the visuals, not just the copy. What's on the site Homepage: A direct hero statement ("I Turn Messy Data Into Decisions") backed immediately by a real dashboard screenshot from my Anomaly Review & Action Console, followed by a "recent work" section pulling in three separate real projects. Services page: Four core offerings — Anomaly Detection Dashboards, Power BI & Data Analytics, AI-Integrated Internal Tools, and Custom Data Automation — each paired with an actual screenshot of that specific project (not a mockup). About page: A short, direct bio and a real photo, no filler. Contact page: A simple inquiry form paired with a data-visualization graphic that matches the site's overall theme. How I used Finish Layer Block Animations: I used on-appear and on-scroll triggers (Reveal and Slide styles) across the homepage, services, and contact pages. Section headings reveal as the page loads, and content blocks slide/fade in as the visitor scrolls — this turns what would be a static, all-at-once page into a guided, paced experience. Block Transform: Rather than a flat grid, I applied a subtle rotation to a couple of key visuals (a dashboard screenshot and the contact-page graphic) — just a few degrees, enough to break the rigidity of the layout without sacrificing readability. It gives the page an asymmetrical, more intentional feel instead of looking templated. Process I built this using Squarespace's Blueprint AI to get a fast base structure, then went through every page replacing AI-generated placeholder content (stock imagery, generic service descriptions, an accidental product/ecommerce section) with real project data, real screenshots, and copy that actually reflects how I work with clients. The site is password-protected rather than published on a paid plan, and is fully responsive across desktop and mobile. Access: 🔗 Site: https://pike-megalodon-4yb2.squarespace.com (https://pike-megalodon-4yb2.squarespace.com)🔑 Password: Omega
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Cover image for Retail Store Sales Analysis (SQL + Tableau) I built a sales ...
Retail Store Sales Analysis (SQL + Tableau) I built a sales analytics project for a fictional retail chain, OmegaEnterprise, to analyze revenue performance, customer behavior, and inventory trends using SQL and Tableau. Project Goals Identify top customers and best-selling products Analyze monthly sales trends and city-wise performance Monitor inventory levels to support stock decisions What I Did Joined Customers, Products, Sales, and Inventory tables using SQL Used aggregations, subqueries, and CTEs to generate insights Prepared datasets and created Tableau dashboards Key Insights Identified top revenue-contributing customers Highlighted high-demand products with inventory shortages Tools used: SQL, Tableau
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Cover image for Anomaly Review & Action Console (Retool + AI)
Anomaly Review & Action Console (Retool + AI)
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Dash Plotly(1)
IRENE MAINA's avatar
IRENE MAINA
Nairobi, Kenya
Data Analyst provided data driven decisions to stakeholders.
24
Followers
Data Analyst provided data driven decisions to stakeholders.
Cover image for House Price Analysis for Value Improvement
House Price Analysis for Value Improvement
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Cover image for Tanzanian Water Well Data Analysis Project
Tanzanian Water Well Data Analysis Project
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Cover image for https://github.com/Brene-m/AWS_Restatrt
https://github.com/Brene-m/AWS_Restatrt
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Cover image for Call Volume Prediction Model for Mtoto News
Call Volume Prediction Model for Mtoto News
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AKHILESH YADAV's avatar
AKHILESH YADAV
Kolkata, India
Data Science | Mathematics Tutor| AI Automations
Data Science | Mathematics Tutor| AI Automations
Cover image for Time Series Analysis on Chicago Taxi Trips
Time Series Analysis on Chicago Taxi Trips
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Cover image for CineMatch-Engine: A High-Performance Movie Recommendation System
CineMatch-Engine: A High-Performance Movie Recommendation System
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Cover image for Real Estate Price Prediction and Recommendation System
Real Estate Price Prediction and Recommendation System
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