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Manideep racharla's avatar
Manideep racharla
Overland, USA
Data Analyst turning Data insights into business impact.
5.0
Rating
2
Followers
Data Analyst turning Data insights into business impact.
Cover image for Optimizing Home Delivery in Small Grocery Stores
Optimizing Home Delivery in Small Grocery Stores
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3
Cover image for Parking Lot Utilization Analysis Dashboard
Parking Lot Utilization Analysis Dashboard
2
22
Cover image for Predictive Analysis of Airline Delays Using Machine Learning
Predictive Analysis of Airline Delays Using Machine Learning
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2
Cover image for Stock Price and Trading Indicators Analysis
Stock Price and Trading Indicators Analysis
0
0
Keras(1)
Anurag Nagare's avatar
Anurag Nagare
Mumbai, India
I’m an AI & Machine Learning engineer with expertise in deve
New to Contra
I’m an AI & Machine Learning engineer with expertise in deve
Cover image for I recently built an AI-powered Mental Health Screening & Cli...
I recently built an AI-powered Mental Health Screening & Clinical Support System designed to assist both individuals and healthcare professionals in early detection and intervention. The system combines patient-reported questionnaires (PHQ-9 & GAD-7) with advanced NLP-based text analysis to assess depression, anxiety, and crisis risk levels. Based on the results, it generates personalized recommendations, safety plans, and professional referral letters, ensuring timely access to the right resources. This solution addresses a critical real-world problem: the growing gap in mental health care access. Many individuals experience symptoms but delay seeking professional help. Ultimately, it helps reduce the risk of untreated mental health crises and improves overall care outcomes.
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50
Cover image for It all started on a
It all started on a Sunday at the AWS User Group Mumbai meetup. I wasn't expecting to walk away with a new obsession, but then the speaker introduced me to Temporal and everything changed. Temporal is a durable execution engine that solves one of the hardest problems in agentic AI what happens when your LLM workflow crashes mid-run? Normally you lose everything So I went home and built this: an agent that monitors your competitors around the clock tracking pricing changes, product launches, hiring signals, and strategic moves. Every 24 hours it uses Mistral (running fully on-device via Ollama) to analyze the data and synthesize a structured executive briefing delivered straight to your inbox. Sometimes the best projects start with a Sunday conversation. https://github.com/AnuragNagare/Agentic-AI-.git
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8
Cover image for HybridAlpha (Hybrid RAG) : One tool
HybridAlpha (Hybrid RAG) : One tool digs into actual SEC filings, not just static documents. From EDGAR, it grabs 10, Ks and 10, Qs fresh each time. Sections like MD&A or Risk Factors get split out by name during parsing. Storage happens two ways at once: words go to ChromaDB, numbers land in SQLite. When a question arrives, the router decides, tone, driven, number, heavy, or both. Depending on that choice, the query moves to one place, sometimes both. Context flows forward only after sorting is done. Answers come from Llama 3.3 70B via Groq, always tagged with sources. Each output ties back to where the data lived. Start by asking, What risks did Apple highlight regarding AI rivals? Out comes exact quotes pulled straight from official documents.
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Cover image for A Neural Network Visualization
A Neural Network Visualization Tool that demystifies AI! I built an interactive web application using Flask and PyTorch that doesn't just recognize handwritten digits it shows you exactly how the AI "thinks." When you draw a digit (0-9) on the canvas, the app processes it through a Convolutional Neural Network and generates a real-time visualization of every layer: from edge detection in the first convolutional layer, through pattern recognition, pooling, and feature extraction, all the way to the final classification. The tech stack includes Python, Flask, PyTorch, and vanilla JavaScript for the frontend. What makes this unique is the educational aspect each layer's activations are visualized using matplotlib, showing the 32 filters in Conv Layer 1, the 64 filters in Conv Layer 2, and the 128-neuron fully connected layer.
1
32
Keras(1)
Dylan Guidry's avatar
Dylan Guidry
Canada
Senior Software Engineer | 10+ Yrs Across Industries
7
Followers
Senior Software Engineer | 10+ Yrs Across Industries
Cover image for AI-Powered COVID-19 Detection via Chest X-Rays
AI-Powered COVID-19 Detection via Chest X-Rays
1
1
Cover image for AI-Powered Produce Inspection System
AI-Powered Produce Inspection System
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2
Cover image for Forge SoftwareHub - Applied AI Development for Web, Mobile & Bl…
Forge SoftwareHub - Applied AI Development for Web, Mobile & Bl…
1
1
Cover image for AI-Powered Deposition Summaries for Legal Cases
AI-Powered Deposition Summaries for Legal Cases
1
18
Keras(2)
MoonTech OneSixEight's avatar
MoonTech OneSixEight
Almelo, Netherlands
Tech Renaissance Leader: AI, FinTech, Web
Tech Renaissance Leader: AI, FinTech, Web
Cover image for Multi-MT5 Integrated, AI-Infused Financial Sentiment Engine
Multi-MT5 Integrated, AI-Infused Financial Sentiment Engine
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16
Cover image for QuantumTrade ML Suite
QuantumTrade ML Suite
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39
Cover image for AI MCQ | FIFA
AI MCQ | FIFA
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10
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Keras(1)