You will get an NLP solution for sentiment analysis, text classification, or NER
Project details
I build NLP systems that extract meaning from text — whether that's analyzing customer sentiment, classifying support tickets, detecting named entities, summarizing documents, or building topic models. My approach combines classical NLP techniques with modern Transformer models (BERT, GPT) to deliver solutions that are both accurate and production-ready.
I've built a real-time financial news intelligence system using BERT sentiment analysis, LDA topic modeling, and Transformer summarization, along with a customer support auto-response system using Seq2Seq with LSTM. I bring the same rigor to every project.
I've built a real-time financial news intelligence system using BERT sentiment analysis, LDA topic modeling, and Transformer summarization, along with a customer support auto-response system using Seq2Seq with LSTM. I bring the same rigor to every project.
Machine Learning Tools
Amazon SageMaker, Apache Spark, Apache Spark MLlib, Azure Machine Learning, BERT, BigDL, ChatGPT, Cloudera, NLTK, NumPy, pandas, Python, Python Scikit-Learn, PyTorch, scikit-learn, SciPy, Scrapy, SQL, Stanford CoreNLP, TensorFlow, TextBlob, Vertex AI, Word2vec, XGBoostWhat's included
| Service Tiers |
Starter
$150
|
Standard
$300
|
Advanced
$850
|
|---|---|---|---|
| Delivery Time | 5 days | 10 days | 15 days |
Number of Revisions | 1 | 2 | 3 |
Number of Model Variations | 1 | 3 | 5 |
Number of Scenarios | 1 | 2 | 4 |
Number of Graphs/Charts | 2 | 5 | 8 |
Model Validation/Testing | |||
Model Documentation | - | ||
Data Source Connectivity | - | ||
Source Code |
Optional add-ons
You can add these on the next page.
Additional Language Support
(+ 3 Days)
+$100
Interactive Dashboard
(+ 3 Days)
+$150
API Endpoint
(+ 2 Days)
+$125Frequently asked questions
About Orbin
AI/ML Engineer | Deep Learning, NLP & Computer Vision | End-to-End Mod
Kozhikode, India - 1:29 am local time
My strongest areas include NLP (sentiment analysis, text generation, sequence-to-sequence models), computer vision (CNNs, CycleGANs), and classical ML (regression, classification, clustering, time series forecasting). I've built projects using PyTorch, TensorFlow, Scikit-Learn, LangChain, and PySpark, and I'm comfortable working with tools like Docker, GitHub Actions, and cloud services for MLOps workflows.
Some highlights from my project work: a real-time NLP pipeline for financial news intelligence using BERT, LDA, and Transformer summarization; a CycleGAN for unpaired face sketch-to-photo translation; a full CI/CD ML API with Prometheus/Grafana monitoring; and an Apache Spark ETL pipeline for churn prediction. I focus on writing clean, well-documented code and delivering results that are practical and measurable.
I'm responsive, detail-oriented, and genuinely passionate about solving problems with data. If your project involves building, improving, or deploying an ML/DL system, I'd love to hear about it.
Steps for completing your project
After purchasing the project, send requirements so Orbin can start the project.
Delivery time starts when Orbin receives requirements from you.
Orbin works on your project following the steps below.
Revisions may occur after the delivery date.
Requirements & Data Assessment
Understand your text data, use case, and target output
Text Preprocessing
Tokenization, stemming/lemmatization, stopword removal, spell correction