Freelance AI Model Developers in Irvine
Freelance AI Model Developers in Irvine
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Vincent Pasili
pro
Nairobi, Kenya
Software Engineer | DevOps & Infra | Replit Services
$50k+
Earned
44x
Hired
5.0
Rating
110
Followers
Expert
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Software Engineer | DevOps & Infra | Replit Services
0
Development of Invite-Only Trading Platform for QEdge Capital
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0
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Development of Bumbu E-commerce Platform for Organic Groceries
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1
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Custom Operations CRM for DVG Operations
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1
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Development of CryptoTipX Digital Tipping Platform
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0
AI Model Developer
(1)
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Ronailson Garcia de Morais
Brasília - Brasilia, Brazil
Senior AI && Fullstack Developer
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Senior AI && Fullstack Developer
1
3D reconstruction
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6
0
Arabic OCR for Identity Card Recognition
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6
2
Real Time Object Detection using Jetson Nano
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28
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Profit Pioneers
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15
AI Model Developer
(3)
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Paolo Perrone
Italy
AI + Data Copywriter & Consultant
$1k+
Earned
1x
Hired
3
Followers
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AI + Data Copywriter & Consultant
1
AI: Transforming Industries, Shaping the Future
1
35
1
Exploring Vector Databases: Empowering AI Applications
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41
0
LinkedIn Ghostwriter & Content Creator
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81
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Navigating the Data Chaos A Guide for Non-Technical Founders
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28
AI Model Developer
(2)
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Karan Singh
Kangra, India
AI/ML Engineer crafting intelligent systems & AI solutions.
10
Followers
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AI/ML Engineer crafting intelligent systems & AI solutions.
0
Scientific Image Forgery Detection — Kaggle Competition Participated in the ongoing Kaggle competition on Copy-Move Forgery Detection in Scientific Images, aimed at identifying manipulated biomedical figures that can compromise research integrity. For this challenge, I developed a ResNet50 + U-Net hybrid segmentation model using PyTorch, designed to detect and segment forged regions at the pixel level. My approach combines Dice and Focal losses for balanced training, WeightedRandomSampling to oversample forged images, and Test-Time Augmentation (TTA) to improve prediction robustness. Achieved an initial score of 0.303 on the public leaderboard. I’m continuing to experiment with architecture tuning, learning rate schedules, and other loss functions to further enhance performance and generalization.
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57
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In this project, I developed a Sentiment Analysis Web App using deep learning (CNN) and traditional models to classify text sentiment with high accuracy. The system includes a complete evaluation pipeline comparing CNN, LSTM, Logistic Regression, Random Forest, and Naive Bayes — analyzing performance across multiple iterations and datasets. Key Highlights: Built a Streamlit-based web app for real-time sentiment classification Developed and evaluated multiple models for accuracy and F1-score Created detailed analysis reports and prototype schematics Project here → GitHub Repository (https://github.com/Imkaran04/Sentiment_Analysis_Web_App/tree/main) Reports: Sentiment Analysis Report (PDF), Product Prototype Diagram Tech Stack: Python, Streamlit, TensorFlow/Keras, Scikit-learn, Matplotlib
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30
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I recently fine-tuned the Mistral 7B Instruct model on a dataset of NDA (Non-Disclosure Agreement) documents — building an AI reviewer capable of identifying compliance issues and clause inconsistencies. To make the model more accessible, I converted the trained weights to CPU-compatible files, allowing efficient inference without GPU requirements. Model: Mistral 7B Instruct v0.1 Focus: Legal text review & semantic understanding Tech: PyTorch, Transformers, Kaggle Check out the full notebook here → [Kaggle Project Link (https://www.kaggle.com/code/karansingh123456/nda-reviewer-model-training)] My Kaggle account here → Profile (https://www.kaggle.com/curiouscyborgs) #AI #NLP #SentimentAnalysis #DeepLearning #CNN #LSTM #DataScience #GitHub
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Introducing QuickSynopsis, a fully-featured AI-based summarization and text comparison web app designed for speed, simplicity, and scalability. This project lets users: Generate efficient, context-aware summaries for any text. Compare multiple Summaries to highlight key differences. Enjoy a responsive UI with user authentication. Built using Python (Flask), HTML/CSS/JS, and SQLite/MySQL, QuickSynopsis can easily be customized or deployed to your preferred cloud platform. Key Features: AI-powered summarization & text comparison Signup/login authentication Integrated payment gateway (customizable) Responsive, modern UI/UX Ready-to-deploy setup for Heroku, AWS, or local hosting Explore the repo: GitHub – QuickSynopsis-Version-Control (https://github.com/Imkaran04/QuickSynopsis-Version-control)
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32
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MoonTech OneSixEight
Almelo, Netherlands
Tech Renaissance Leader: AI, FinTech, Web
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Tech Renaissance Leader: AI, FinTech, Web
0
QuantumTrade ML Suite
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39
0
Multi-MT5 Integrated, AI-Infused Financial Sentiment Engine
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16
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AI MCQ | FIFA
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10
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Ali Hassan
Rawalpindi, Pakistan
Transforming Data into Actionable Insights 🔍
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Transforming Data into Actionable Insights 🔍
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SALES PREDICTION USING PYTHON
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217
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IRIS FLOWER CLASSIFICATION
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116
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Titanic Analysis Project
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47
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Bikes Sales Analysis
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237
AI Model Developer
(2)
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Hamza Mooraj
Karachi, Pakistan
Applied AI Engineer | LLM Fine-Tuning & RAG
New to Contra
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Applied AI Engineer | LLM Fine-Tuning & RAG
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Multimodal Medical QA Assistant with RAG
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0
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Vision-Model Benchmarking for Crop Disease Classification
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1
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Diabetes Risk Prediction with Neural Networks
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0
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AI Learning Buddy – RAG Academic Assistant
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0
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Waruna Srinath
Colombo, Sri Lanka
Senior Machine Learning Engineer and Data Scientist
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Senior Machine Learning Engineer and Data Scientist
0
Automated the Camera light of Jetson robot for surgeries
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20
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LLMs Fine Tuning for Specific Use Cases
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16
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3D Data Science Knowledge Graph Visualization
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21
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