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I will build custom nlp and sentiment analysis models in python
AI and ML Engineer
Hi, I'm Atta! I'm an AI & Machine Learning Engineer specializing in turning raw data into working software. Whether you need predictive ML models, custom NLP audio pipelines (like Whisper & VADER), or...
About this Gig
Are you looking to analyze text or audio data, transcribe speech, or build custom AI classification models? You are in the right place!
I am a Machine Learning Engineer specializing in NLP, Text Analytics, and Audio AI in Python. I build end-to-end pipelines tailored to your dataset using modern text and speech libraries.
What I Offer:
- Text & Audio Preprocessing: Tokenization, lemmatization, stop-word removal, cleaning, and audio signal processing.
- Speech & Audio NLP: Audio transcription using OpenAI Whisper, audio feature extraction (MFCCs/Spectrograms with Librosa), and voice data analysis.
- Sentiment Analysis: VADER rule-based sentiment, customer review scoring, and social feedback analysis.
- Text Classification: Topic categorization, spam detection, and intent recognition using Scikit-Learn algorithms (Naive Bayes, Random Forest, XGBoost).
- Local API Integration: Packaging your text or audio pipeline into a lightweight FastAPI endpoint (app.py).
Tech Stack:
- Language: Python
- Libraries: Whisper, Librosa, Scikit-Learn, NLTK, SpaCy, Pandas
- Environment: Google Colab / Jupyter Notebooks (.ipynb)
- API: FastAPI
Please message me with your project details before placing an order!
Programming language:
Python
Frameworks:
Scikit-learn
•
Panda
•
Other
APIs:
Other
Tools:
Jupyter Notebook
•
Colab
My Portfolio
Other Data Science & ML Services I Offer
FAQ
What formats will I receive my final deliverables in?
You will receive a clean, fully commented Google Colab Notebook (.ipynb) or standalone Python scripts (.py), along with trained model files (.pkl / .joblib), audio processing scripts, and model evaluation metrics.
Can you process speech and audio data alongside text?
Yes! I use OpenAI Whisper for high-accuracy speech-to-text transcription and Librosa for audio feature extraction (MFCCs, spectrograms). I can feed transcribed voice data directly into sentiment models like VADER or custom text classifiers.
Do you provide cloud deployment for models or audio pipelines?
No, I do not provide cloud hosting (AWS/GCP/Heroku). However, I can package your complete text or audio processing model into a clean, lightweight local FastAPI script (app.py) ready for local integration.
What dataset or file formats should I provide?
For text data, I accept CSV, JSON, Excel, or TXT formats. For audio processing, you can upload WAV, MP3, or FLAC files directly or share a Google Drive download link.
