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$
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I will do python data science, data cleaning, and machine learning
Technical Developer and Creative Strategist
Technical Developer & Creative Strategist: Hi, I’m Himesh Mehta. I bridge the gap between complex engineering and creative execution. With expertise in Python, AI/ML, and MongoDB, I build efficient, ...
About this Gig
Welcome to my professional Data Science and Python Engineering gig!
Need a developer to clean messy datasets, build robust ML models, or design custom recommendation logic? I deliver clean, production-ready code to unlock insights.
WHAT I OFFER :
1. DATA CLEANING & PREPROCESSING (Pandas, NumPy)
- Structural formatting and type casting
- Handling missing values, duplicates, and outliers
- Feature engineering pipelines
2. EXPLORATORY DATA ANALYSIS (Matplotlib, Seaborn)
- High-quality data charts and statistical overviews
- Correlation and trend identification
3. MACHINE LEARNING & ALGORITHMS (Scikit-Learn)
- Model creation, training, evaluation, and fine-tuning
- Custom logic (including recommendation systems)
4. DEPLOYMENT & DOCUMENTATION
- Clean Jupyter Notebooks (.ipynb) or Python scripts (.py)
- API integration and cloud deployment setup
Please message me before placing an order to discuss your dataset size and technical goals. Let's build something efficient together!
Programming language:
Python
•
SQL
•
Colab
•
NoSQL
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Other
Frameworks:
Scikit-learn
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DeepPy
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SimpleCV
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Panda
•
Other
APIs:
Google Cloud Vision API
•
IBM Watson Visual Recognition
Tools:
Jupyter Notebook
•
OpenCV
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TensorFlow
•
Excel
•
SimpleCV
•
Colab
My Portfolio
FAQ
Q1: What file formats do you accept for the datasets?
A: I accept almost all standard data formats, including CSV, Excel (.xlsx, .xls), JSON, SQL database dumps, and plain text files. If your data is in an unconventional format, please message me first!
Q2: What deliverables will I receive at the end of the project?
A: Depending on your package, you will receive the complete source code as a clean Python script (.py) or a structured Jupyter Notebook (.ipynb) with markdown notes. Higher tiers also include comprehensive model documentation, performance logs, and deployment files.
Q3: Can you work with large-scale or messy business data?
A: Yes, absolutely. I specialize in heavy data preprocessing and structural formatting. I will clean up anomalies, fix internal inconsistencies, and engineer features to make the dataset entirely ready for analysis or model training.
Q4: Do you handle custom machine learning tasks like recommendation systems?
A: Yes! I can build custom machine learning models tailored to your specific application, including classification, regression, clustering, and custom recommendation logic based on your operational data.
