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You will get Custom Text Dataset Creation for NLP & AI Training

Jessie James J.Status: Offline
Jessie James J.
Preview imagePreview image

Let a pro handle the details

Buy Machine Learning services from Jessie James, priced and ready to go.
Jessie James J.Status: Offline
Jessie James J.
Preview imagePreview image

Let a pro handle the details

Buy Machine Learning services from Jessie James, priced and ready to go.

Project details

I build custom text datasets for NLP and AI training, any domain. I specialize in Philippines low‑resource languages but work with English and high‑resource languages too.

My proven pipeline: data sourcing (web scraping or your files) → cleaning & normalization → annotation (sentiment, classification, or custom labels) → quality validation → delivery in CSV/JSON/Parquet with source code and documentation.

Proof: I created HiliSenti v1, the first publicly available sentiment dataset for Hiligaynon (23,337 sentences, 93.5% accuracy, DOI: 10.57967/hf/8737, 117+ downloads).

I work async (chat/email only). Fixed‑price quotes. Free revisions included. Let me know your requirements.
Machine Learning Tools
BERT, ChatGPT, NLTK, NumPy, pandas, Python, Python Scikit-Learn, PyTorch, Scrapy, SQL, TensorFlow, TextBlob, Word2vec
What's included
Service Tiers Starter
$40
Standard
$120
Advanced
$250
Delivery Time 2 days 7 days 14 days
Number of Revisions
122
Number of Model Variations
0
Model Validation/Testing
-
Model Documentation
-
Data Source Connectivity
-
-
-
Source Code
Jessie James J.Status: Offline

About Jessie James

Jessie James J.Status: Offline
Junior ML Engineer | NLP Researcher | Linux Administration
Hinigaran, Philippines - 10:22 am local time
I specialize in Natural Language Processing and Machine Learning, with hands-on experience in building and deploying innovative solutions. As a BSIT graduate, I developed a sentiment analysis model for Hiligaynon, a low-resource language, curating a 22,000-sample dataset and fine-tuning the state-of-the-art XLM-RoBERTa-large. My expertise spans end-to-end ML pipelines, from dataset creation to local LLM deployment and Linux server infrastructure. I’m adept at server setups and managing full stack projects, ensuring seamless deployment on platforms like Hugging Face Hub. With a strong foundation in Python, TensorFlow, and various NLP techniques, I bring technical skills that can elevate your projects. If you’re looking for someone who can transform complex requirements into impactful solutions, let's connect and discuss how I can contribute to your goals.

Steps for completing your project

After purchasing the project, send requirements so Jessie James can start the project.

Delivery time starts when Jessie James receives requirements from you.

Jessie James works on your project following the steps below.

Revisions may occur after the delivery date.

1. Data Sourcing

Collect raw text from provided files, web scraping, or APIs. Deliver a raw data log.

2. Data Cleaning & Normalization

Deduplicate, fix encoding, normalize text (lowercase, punctuation, abbreviation expansion). Provide cleaned dataset.

Review the work, release payment, and leave feedback to Jessie James.