Freelance Software Engineers in MaharashtraFreelance Software Engineers in Maharashtra
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Supreet S's avatar
Supreet S
proMumbai, India
AI-Native Creative Director: Brand, UI/UX & Motion
$1k+
Earned
1x
Hired
5.0
Rating
88
Followers
JITTER_EXPERT

expert

KITTL_EXPERT

expert

+5
AI-Native Creative Director: Brand, UI/UX & Motion
Cover image for Chat App UI for Synapse
Chat App UI for Synapse
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1
Cover image for Monochrome SaaS Dashboard UI Design
Monochrome SaaS Dashboard UI Design
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2
Cover image for Single-Screen Weather App Development
Single-Screen Weather App Development
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10
Cover image for Logo Design Exploration for Nia B. Studio
Logo Design Exploration for Nia B. Studio
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5
Software Engineer(2)
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 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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90
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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150
Cover image for What your attention heatmap isn't
What your attention heatmap isn't telling you Everyone's staring at attention heatmaps and calling it "interpretability." Almost nobody's asking whether a single attention map actually tells you what the model used to make its decision. It doesn't. Not on its own. A raw attention map from layer 8 shows you what layer 8 attended to. It says nothing about how that signal got mixed, diluted, or overwritten by every layer before and after it. Attention rollout fixes this — and I built a walkthrough to show why it matters. Here's what makes it more than a "pretty heatmap" demo: Instead of visualizing one layer's attention, I traced how information actually flows through the full transformer stack. → Every layer's attention matrix is extracted, per head, per token → Multi-head attention is averaged, then combined with the residual connection (identity + attention) — this is the step most tutorials skip, and it's the one that actually matters → The combined matrices are matrix-multiplied layer by layer, rolling attention forward from input to output → The result: a single map showing genuine token-to-token influence across the entire network, not just one layer's snapshot The overlay shows you everything: → Per-layer attention vs. rolled-out attention, side by side → Token importance scores overlaid directly on the input text → A comparison view: which tokens raw attention says "matter" vs. which ones rollout says actually matter → Head-level breakdown so you can see which heads specialize vs. which are noise No black box. No "trust me, the model looked here." Just linear algebra, applied honestly across every layer instead of cherry-picking one. Built with PyTorch + HuggingFace Transformers + Matplotlib. Runs on any pretrained transformer, fully offline. ⚠️ Important: attention rollout is an approximation, not ground truth. It assumes attention is the primary information pathway, which ignores MLP layers and can still mislead for very deep models. Treat it as a debugging lens, not proof of causality.
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Software Engineer(2)
Ariston IT Services's avatar
Ariston IT Services
Pune, India
Ariston IT: Elevate Your Business with Custom Software
Ariston IT: Elevate Your Business with Custom Software
Cover image for Tour & Guide Booking and Management
Tour & Guide Booking and Management
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21
Cover image for Business Listing / Advertising Platform
Business Listing / Advertising Platform
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14
Cover image for Sports Event Booking App
Sports Event Booking App
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12
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Software Engineer(2)
Kamlesh Pokiya's avatar
Kamlesh Pokiya
Mumbai, India
Full Stack Developer | React.js, Node.js, Laravel, SaaS, AI
7
Followers
Full Stack Developer | React.js, Node.js, Laravel, SaaS, AI
Cover image for Delivered an end-to-end AI platform for a client—chat system...
Delivered an end-to-end AI platform for a client—chat system, dashboard, code features, smooth UX. If you need a similar setup, I’m available.
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46
Cover image for Proud to Announce My Latest Full-Stack Build: Flowyze! I rec...
Proud to Announce My Latest Full-Stack Build: Flowyze! I recently developed Flowyze — a powerful, end-to-end platform built using modern full-stack technologies. From scalable architecture to smooth UI/UX, every part of this project was crafted to handle real business workflows and deliver a premium experience. 💡 Tech Highlights: ✔ Full-stack architecture (frontend + backend + APIs) ✔ High-performance, scalable system ✔ Secure, clean, and modular codebase ✔ Optimized for real users & business operations If you’re looking to build a SaaS, dashboard, automation tool, or custom web platform, I’d love to help bring your idea to life with the same precision and quality. 💬 Open for new projects — let’s build something powerful!
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Cover image for 🚀 Just shipped a new MERN project! Proud to share TalentsLi...
🚀 Just shipped a new MERN project! Proud to share TalentsList.com (http://TalentsList.com), a modern talent-matching platform I developed using the MERN stack (MongoDB, Express, React, Node). Fast, scalable, and built with clean UI + solid backend architecture. If you're looking to build or revamp your web app, SaaS product, or custom platform, I’d love to help bring your idea to life. Open to new projects — Let’s build something great together!
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Cover image for Over the past few months, I’ve been helping teams streamline...
Over the past few months, I’ve been helping teams streamline and scale their operations using n8n — and the results have been amazing. From cutting repetitive tasks to building full logic-driven systems, n8n has become my go-to tool for smart, scalable automation. 🔧 What I Build with n8n 1️⃣ Multi-step, logic-heavy automations 2️⃣ Deep API integrations (REST, OAuth2, custom logic) 3️⃣ Lead capture → CRM workflows 4️⃣ Stripe, Notion, Slack, Airtable & more 5️⃣ Error-handled, production-grade processes 6️⃣ Real-time alerts & webhook-driven flows 💡 Why n8n? - Open-source, flexible, and highly customizable - Scales without pricey SaaS tools - Great for businesses wanting automation built their way - Integrates with almost anything If you’re looking to automate or upgrade your workflows, I’d be happy to help.
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Software Engineer(4)
Aniket Ghavte's avatar
Aniket Ghavte
Pune, India
AI-Native Full Stack Engineer
New to Contra
AI-Native Full Stack Engineer
Cover image for I shipped an open-source package
I shipped an open-source package called Fold. Here's the problem it solves: When you build an AI agent that touches more than one data source S3, Slack, a local database, your filesystem you end up managing three or four different SDKs, auth flows, and API shapes before writing a single line of actual agent logic. Then you give your LLM a list of 12 tools and hope it picks the right one. Fold takes a different approach. It's a virtual filesystem. You mount any backend under a path prefix: /notes → your local Documents folder /db → a SQLite database /s3 → an S3 bucket /slack → Slack channels as directories /model → a locally running Ollama model Your agent gets one tool: bash. cat, ls, grep, wc, head, pipe across all of them. LLMs were trained on bash. They know it cold. Fold exploits that instead of fighting it. Three things I built that Mirage (the main prior art) doesn't have: Local-first. SQLite, local files, and Ollama are first-class resources. Everything can run on-device with zero data egress and zero API keys. Reactive. ws.watch (http://ws.watch)() lets any resource push events when data changes. Your agent triggers automatically no polling, no cron. Rich listings. ls -c returns metadata alongside filenames row counts, schemas, member counts, last activity. The agent understands the environment in one call instead of five. It also ships as an MCP server out of the box. One file and it's available in Claude, Cursor, or any MCP client. Published under The Builder Company: npm install @tbc-fold/node Repo: https://lnkd.in/g6EdaYEx (https://lnkd.in/g6EdaYEx)Website: https://lnkd.in/g6WjxGGd Built this alongside Aura. The two are related Fold is the abstraction that lets Aura's local agent work across your data without sending anything to the cloud. If you're building agents and hitting the multi-SDK problem, try it.
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Cover image for DQN Web3 Growth Engine
DQN Web3 Growth Engine
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3
Cover image for Bango Payments
Bango Payments
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0
Cover image for AURA an AI native browser
AURA an AI native browser - which thinks and becomes your second brain fr..
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Software Engineer(5)
Deion Dsouza's avatar
Deion Dsouza
Kolhapur, India
Software Engineer building user friendly software
Software Engineer building user friendly software
Cover image for AI-Powered Waste Segregation and Management System
AI-Powered Waste Segregation and Management System
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8
Cover image for Real-Time Bus Crowding Monitoring System
Real-Time Bus Crowding Monitoring System
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3
Cover image for Oasis - Event Management System
Oasis - Event Management System
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8
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Software Engineer(3)