NLP AI Development

@sajjadtaghvaeifr

Hello, I trust you're doing well. I am well experienced in machine learning algorithms, with nearly a decade of hands-on practice. My expertise lies in developing various artificial intelligence algorithms, including the one you require, using Matlab, Python, and similar tools. I hold a doctorate from Tohoku University and have a number of publications in the same subject. My portfolio, which showcases my past work, is available for your review. Your project piqued my interest, and I would be delighted to be part of it. Let's connect to discuss in detail. Warm regards. please check my portfolio link: https://www.freelancer.com/u/sajjadtaghvaeifr

@koolvishruth

Hello, I am Vishruth from Bangalore I am Machine Learning engineer with 7 years of experience in NLP, model development and REST APIs .I can work and deliver this project. Lets connect

@vasudharao9

Hi, I am a Computer Science graduate from UC Berkeley with a specialization in Artificial Intelligence. I have more than 10 years of experience in AI and can help you with this project. Thanks

@snbhanja

Hi, I have worked on many end to end NLP solutions using trained NLP models like BERT, DeBerta as well as open source small LLMs from Meta lika llama, deepseek etc. The usecases mostly include sentiment analysis, chatbots, custom entites extraction, summarisation, question answering etc. I can finetune a NLP model on your data. Based on your usecase I can decide the best model to start with. I will make the REST API with easy deployment using docker for your server. Let me know.

@mayankinnovative

Hello! I'm excited to help you build an end-to-end Natural Language Processing solution. Project Understanding: You need a reliable NLP model that handles free-form language, with flexible task sets, including text generation, sentiment analysis, or entity extraction. Approach: 1. Technical discovery call to define task sets and requirements. 2. Data collection and preprocessing, leveraging pre-trained models (BERT, spaCy). 3. Model development using PyTorch or TensorFlow, focusing on transformer architectures. 4. API development using Flask or FastAPI, with REST or GraphQL endpoints. 5. Deployment and testing, with clear documentation and demo. Relevant Experience: With 15+ years of experience in NLP and machine learning, I've developed similar solutions, leveraging deep learning and transformer models. "Let's create an intelligent NLP solution that unlocks insights from your text data!"

@chiragardeshna

Hello there, I deliver end-to-end NLP solutions using Python + PyTorch + Hugging Face, packaged behind a clean FastAPI endpoint you can plug into any frontend. You’ll get: • A fine-tuned NLP model (generation, classification, or entity extraction). • A lightweight REST API (FastAPI) with /predict and /health. • Docker setup + clear instructions + short demo video. Tech stack: PyTorch, Transformers, FastAPI, Docker. MVP timeline: 7–10 days once data + task are confirmed. Recent work available on request. Regards Chirag

@malkesh3m

⭐ Hello there, My availability is immediate. I read your project post on Python Developer for NLP AI Development. We are experienced full-stack Python developers with skill sets in: Python, Django, Flask, FastAPI, Jupyter Notebook, Selenium, Data Visualization, ETL AI/ML & Data Science: Model development, training & deployment, NLP, Computer Vision, Predictive Analytics, Deep Learning React, JavaScript, jQuery, TypeScript, NextJS, React Native NodeJS, ExpressJS Web App Development, Web/API Scraping API Development, Authentication, Authorization SQLAlchemy, PostgresDB, MySQL, SQLite, SQLServer, Datasets Web hosting, Docker, Azure, AWS, GCP, Digital Ocean, GoDaddy, Web Hosting Python Libraries: NumPy, pandas, scikit-learn, TensorFlow, PyTorch, etc. Please send a message so we can quickly discuss your project and proceed further. I am looking forward to hearing from you. Thanks

@dushyant317

I bring 13 years of professional experience delivering high-quality results. I have strong expertise in all the required skills listed for this project. My approach ensures accuracy, clear communication, and timely delivery. I am confident I can exceed your expectations with efficient, reliable work. Looking forward to contributing to your project—ready to begin immediately.

@habebaftooh

I hold a B.Sc. in Artificial Intelligence, and I’ve delivered several end-to-end NLP systems that turn raw text into accurate, context-aware outputs using modern deep-learning techniques. My background includes building intelligent pipelines for text generation, sentiment analysis, entity extraction, and custom classification models integrated with clean, reliable APIs ready for production use.I approach NLP projects by designing models that genuinely understand context, adapt to different language tasks, and remain stable under real-world usage. My workflow focuses on clean architecture, efficient training, and reliable deployment ensuring the system performs intelligently whether it’s generating text, interpreting sentiment, or extracting structured insights from unstructured input. I also package everything in a way that’s easy to integrate and extend, so you can evolve the solution without friction as your requirements grow.

@paruls154

Hi With over a decade of experience under my belt, I am excited to bring my expertise in Java and wide range of modern frameworks to deliver a top-notch, end-to-end NLP solution for your business. Understanding the flexibility required in this project, my primary goal will be to develop and train a robust NLP model (preferably using Python, PyTorch or TensorFlow) that not only effectively handles free-form language but also encompasses tasks like generating coherent replies, classifying sentiments or extracting entities. Trust me as your dedicated partner in this project - together we'll find creative yet efficient solutions for your complex NLP challenges! Let's connect and transform your expectations into tangible results. Regards Parul Saini

@himanshus642

Leveraging my extensive experience as an AI Developer, particularly in the field of Natural Language Processing (NLP), I'm confident that I can build a powerful end-to-end solution for you. My approach centers on deploying AI systems that automate tasks and enhance user experiences using clean, well-documented code- an ideal fit for your project. Proven by my past projects with OpenAI, LangChain, RAG and custom knowledge bases, I have demonstrated the ability to handle your specific requirements. Drawing upon my advanced skills in Python and platforms like PyTorch and TensorFlow, I will construct a high-performance NLP model tailored to your needs. Moreover, considering your intention to use either REST or GraphQL API for frontend integration, I assure you that my expertise in FastAPI and Flask will be valuable here. Additionally, given my proficiency in Cloud Deployment with AWS, Google Cloud and Azure, I'll ensure a seamless setup process on your existing hosting. My effective communication skills will facilitate our collaboration while providing a quick turnaround time. Rest assured that the end result will be a reliable NLP solution packed with clear setup instructions and supporting materials to ensure your satisfaction. Let's harness the power of AI and build something intelligent together!

@VirasatSolutions

Hello, I can deliver a complete, production-ready NLP solution that transforms raw text into context-aware outputs such as text generation, sentiment classification, and entity extraction. After a short discovery call, I’ll finalize the exact task scope and success metrics. + What you’ll receive • A trained NLP model in Python (PyTorch or TensorFlow) with clean, documented code • A lightweight REST API (FastAPI) or optional GraphQL endpoint • Full setup instructions plus a short demo video / live walkthrough • Model checkpoint and reusable training pipeline + Proposed Approach • Discovery (1–2 days): Define tasks, data availability, accuracy targets • Data Prep (2–4 days): Clean, validate, and augment datasets if needed • Model Training (4–8 days): Fine-tune transformer-based models for your use case • API Development (2–4 days): Wrap model for real-time inference • Testing & Handover (1–2 days): Performance tuning, validation, final demo + Tech Stack • PyTorch / TensorFlow • Hugging Face Transformers • FastAPI / Docker Estimated MVP Timeline ✅ 2–3 weeks depending on data and task complexity. + From You • Sample data • Hosting details • Priority tasks (generation, classification, NER, etc.) I’m ready to start immediately and can provide regular progress updates. Let’s schedule a quick discovery call to finalize scope and timeline.

@sakshitiwari2323

➡️ NLP AI Development – End-to-End Intelligent Text Solution Having meticulously evaluated your project, I’m ready to deliver a production-grade, context-aware NLP engine that turns raw free-form text into accurate, actionable insights — fully API-ready and tailored to your final use case. ✅ My Blueprint ✔ Core Model ➡️ Fine-tuned IndicBERT / mBERT / Llama-3-8B-Instruct (your choice) for Hindi + English ➡️ Multi-task ready: entity extraction, sentiment, intent classification, generative replies ✔ API Layer ➡️ FastAPI + Uvicorn → blazing-fast REST/GraphQL endpoint (<50ms inference) ➡️ Async batch support, rate-limiting, JWT auth ✔ Performance & Scalability ➡️ ONNX + TorchScript export for CPU/GPU speed ➡️ Dockerized + ready for your existing server (one-click deploy) ✔ Delivery ➡️ Complete Python codebase + trained model weights ➡️ Swagger/OpenAPI docs + 10-minute Loom walkthrough + live demo ➡️ 12–18 days to fully working MVP ✅ Solution Framework ➲ Python + Transformers + Sentence-Transformers ➲ FastAPI + Pydantic v2 + PostgreSQL vector store (optional) ➲ Docker + NVIDIA/CUDA support ➽ Let’s jump on a quick call, lock the exact tasks, and I’ll deliver your intelligent NLP brain — fast, accurate, future-proof! ~Sakshi.V

@rushikeshc44

Hi there, I can deliver an end-to-end NLP solution exactly as described. After a short discovery call, I will finalize whether you need sentiment analysis, text generation, NER, or a combination. My approach: Use state-of-the-art transformer models (BERT, DistilBERT, or T5) Fine-tune using your sample data or recommended datasets Wrap the model into a clean Python codebase (PyTorch/TensorFlow) Expose a lightweight REST API using FastAPI Provide a full setup guide + a walk-through video demo Help you integrate it with your existing hosting Tech Stack: Python, PyTorch, Transformers, FastAPI, Pandas, NumPy, Docker (optional) Timeline: 3–5 days for a working MVP. I’d love to jump on a quick call to confirm the exact tasks and get started immediately.

@bizvivo

Greetings, With a robust background in statistics and data science, complemented by a prolific academic writing portfolio, I am well-equipped to tackle complex data-driven challenges. My expertise is rooted in the successful completion of numerous PhD-level thesis projects, where I employed advanced statistical methodologies to extract meaningful insights from diverse datasets. My professional journey has been marked by collaborations with various companies, leading to projects that demanded high-level quantitative analysis and data interpretation. These projects enabled me to delve into trend analysis, temporal behaviour studies, and comparative assessments of data variables. I possess proficiency in a suite of analytical tools, including SPSS, R, Python, OpenCV, WEKA, Tableau, Power BI, and Excel. My skill set extends to sophisticated techniques such as image processing, machine learning, deep learning, artificial intelligence, natural language processing, hypothesis testing, forecasting, T-tests, and ANOVA, among others. I am eager to engage in discussions that leverage my comprehensive skill set to provide innovative solutions in AI and ML domains. Warm regards, Radhika

@Mudassar295

Hello, I am an AI Engineer with 1 year of hands-on experience in NLP and deep learning. I can build an end-to-end NLP solution tailored to your needs—whether it involves text generation, sentiment analysis, or entity extraction. I will deliver a well-trained model in Python using PyTorch or TensorFlow, wrapped in clean, maintainable code. The solution will include a lightweight REST or GraphQL API for seamless integration with your front-end. I can also provide setup instructions, a walkthrough demo, and recommendations for additional datasets or pre-trained checkpoints to accelerate results. I aim to deliver a working MVP efficiently and reliably. Feel free to contact with me. Best Regards, Mudassar Niaz

@karthikresonite

Hi, I can deliver a complete end-to-end NLP solution that processes raw text and returns accurate, context-aware outputs. After a short discovery call, I’ll help you define whether the primary task is generation, sentiment analysis, entity extraction, or a mix of all three. My proposed approach: • Build on Python with PyTorch/TensorFlow, using strong pretrained checkpoints (BERT, RoBERTa, T5, or similar) fine-tuned on your sample data. • Wrap the model in a clean, documented micro-service with a REST or GraphQL API so your web, mobile, or desktop front end can plug in instantly. • Implement robust preprocessing, inference optimisation, and optional batching/caching for fast response times. • Provide straightforward setup instructions plus a walkthrough demo to ensure everything runs smoothly on your hosting. You’ll receive a working MVP with a trained model, commented code, and deployment-ready API. Ready to start as soon as we confirm scope and sample data. Best Regards, Resonite Technologies

@Ashadb

I have mainly worked on NLP and i have strong understanding of LLMs and Machine Learning Models, I have worked with a client from Qualcomm and built AI Agents for them to use in NLP One agent was a AI VLSI Agent which help the engineers compare Projects and analyze them to help them in their development process and I have also worked on Machine Learning models to analyze mental health using journal diaries for a company and it is in their app now

@shadinbm

What I will deliver MVP model (fine-tuned on your data + appropriate public datasets or checkpoints). Codebase: modular, well-documented Python code for preprocessing, training, inference. API: FastAPI (REST) or GraphQL endpoint for inference with example client calls. Container: Dockerfile and run instructions for easy deployment on your hosting. Evaluation: test suite, metrics (accuracy/F1/ROUGE/BLEU/Hits@K, as appropriate), and a validation report. Demo & Handover: short walkthrough video (screen recording) or live demo; setup & API usage docs; model checkpoint(s). Optional: lightweight monitoring hooks (latency, error logs) and simple script for batch inference.