Freelancers using Dash Plotly in Mumbai
Freelancers using Dash Plotly in Mumbai
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Anurag Nagare
Mumbai, India
I’m an AI & Machine Learning engineer with expertise in deve
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I’m an AI & Machine Learning engineer with expertise in deve
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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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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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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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What every "AI gesture control" demo quietly leaves out Everyone films a hand waving at a screen and calls it AI. Almost nobody shows what's underneath that there's usually no gesture model at all. A "grab" is one distance crossing a line. Here's proof. I built a jigsaw puzzle you solve with your bare hands no mouse, no controller, no gesture classifier, no training.
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Dash Plotly
(3)
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Abu Aasif Ansari
Bhiwandi, India
I build AI agents & internal tools that act on data
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I build AI agents & internal tools that act on data
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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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Ask My Docs — RAG-Based AI Chat Agent
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Sounds Like AI? — AI Writing Authenticity Checker
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CUT Coffee — Brew Your Story I reimagined CapCut as a premium coffee brand for creators. The scissors become a cup mark. The timeline becomes a film-strip sleeve. Every great story begins with a cut. Direction A — CapCut as a Different Industry https://www.linkedin.com/posts/abuaasif_capcutdesignstudio-branddesign-capcut-activity-7467333219772952576-53vt?utm_source=share&utm_medium=member_desktop&rcm=ACoAACRm5rcB0nVG0_HUX6-IXfuWqNGquZ-jMQU
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Dash Plotly
(1)
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Aniket More
Mumbai, India
Data Science/Analysis, Excel, Python, Power Bi, Scikit learn
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Data Science/Analysis, Excel, Python, Power Bi, Scikit learn
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Below is an interactive web based dashboard, using Python pandas, plotly dash. The graphs are interactive and gets updated automatically using the drop down provided.
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Hello All, Below is a sample Dashboard for a sales data prepared using excel. It uses data visualizations in excel and interactive slicers to modify the visuals.
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Here is the Capstone project I have got hands on experience on while completing professional certification course. It web Scrapes data from web for falcon rockets and builds a predictive model using machine learning algorithm using scikit learn model
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This is a practice project I worked on to exclusive on power bi to make a simple dashboard to have an interactive visual, with date sliders. With metrics like revenue per passengers, and passenger by date
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Dash Plotly
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