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English
$
USD
I will build python machine learning deep learning data science and ai projects
Data Analyst , Machine Learning
With 4 years of experience in data analysis and Python development, I help businesses turn raw data into clear, actionable insights — from small CSV cleanups to automation pipelines and predictive mod...
About this Gig
Looking for reliable AI, Machine Learning, Deep Learning, or Data Science solutions in Python? You are in the right place!
I specialize in building production-ready machine learning models, custom neural networks, and comprehensive data analytics pipelines tailored to your needs.
What I Offer:
- Machine Learning: Classification, Regression, Clustering, Random Forest, XGBoost, SVM.
- Deep Learning: Neural Networks (CNN, RNN, LSTM, Transformers) with TensorFlow & PyTorch.
- Data Science & EDA: Data cleaning, feature engineering, and visualization (Pandas, Seaborn, Matplotlib).
- Computer Vision & NLP: Object detection (OpenCV, YOLO), text classification, and sentiment analysis.
- Deployment: API creation (FastAPI/Flask) and web interfaces (Streamlit).
Why Choose Me?
- Clean, well-structured, and fully commented Python code.
- Clear setup documentation for Jupyter Notebook or Google Colab.
- Fast communication and quality-focused delivery.
Programming language:
Python
•
Colab
FAQ
What format should my data be in?
I primarily work with CSV, Excel (.xlsx), and JSON files. However, I can also connect to SQL databases or Google Sheets. If your data is "unstructured" (like a collection of text files), please message me first so we can discuss the preprocessing required.
Do I need to clean my data before sending it to you?
No! Data cleaning and preprocessing are included in all my packages. I will handle missing values, remove duplicates, and perform feature encoding using Pandas and Scikit-Learn to ensure your dataset is ready for high-accuracy modeling.
What specific Machine Learning libraries do you use?
My primary stack includes Scikit-Learn (sklearn) for traditional ML (Random Forest, SVM, Regression) and Pandas/NumPy for data manipulation. For the Premium package, I also use TensorFlow or Keras if your project requires Deep Learning or Neural Networks.
Will I be able to run the code myself?
Absolutely. I deliver the final project as a Google Colab notebook (.ipynb) or a Python script (.py). I include step-by-step comments so that even if you aren't a programmer, you can run the model and see the results with one click.
How do you ensure the model is accurate?
I use professional evaluation metrics such as Accuracy, Precision-Recall, F1-Score, and Mean Squared Error (MSE). For the Standard and Premium packages, I perform Cross-Validation and Hyperparameter Tuning to ensure the model performs well on "unseen" data, not just your current file.
