Browse categories
Explore
Fiverr Pro
English
$
USD
I will build, optimized and evaluate machine learning models
Machine Learning Expert, Predictive Models and Data Cleaning
I am a Machine Learning & AI specialist with strong experience in ML model training, data cleaning, and predictive analytics. I help clients build accurate, reliable models for real-world problems suc...
About this Gig
Is your Machine Learning model overfitting, biased, or failing on real-world data?
Stop relying on "Accuracy" alone. In real-world data science, a model predicting fraud or disease with 99% accuracy is useless if it misses the 1% that matters. You need rigorous, mathematically sound evaluation.
Welcome! I am an AI Engineer specializing in high-precision Machine Learning Classification. I don't just import Scikit-Learn; I apply academic-grade research methodology to engineer, tune, and evaluate predictive models that actually solve business problems.
WHAT I WILL DO FOR YOU:
- Deep Exploratory Data Analysis (EDA): Feature distribution, correlation matrices, and outlier detection.
- Advanced Data Preprocessing: Handling missing values, encoding, and scaling.
- Tackling Imbalanced Data: Expert implementation of SMOTE, ADASYN, and class-weight balancing.
- Multi-Model Benchmarking: Pitting models against each other (Logistic Regression, Random Forest, SVM, KNN, XGBoost, LightGBM).
THE EVALUATION METRICS YOU WILL GET:
- Confusion Matrix (False Positives vs. False Negatives)
- Precision, Recall, and F1-Score
- ROC-AUC Curves & Precision-Recall Curves
- Log-Loss and Classification Reports
Programming language:
Python
Frameworks:
Scikit-learn
•
SimpleCV
•
Keras
•
Panda
Tools:
Jupyter Notebook
•
Excel
•
SimpleCV
•
Colab
FAQ
1. What if my dataset is highly imbalanced (e.g., 99% Class A, 1% Class B)?
I specialize in imbalanced classification. I use techniques like SMOTE (Synthetic Minority Over-sampling Technique) and evaluate the model strictly on F1-Score and Precision-Recall AUC, not misleading standard accuracy.
2. Will you explain the code and the results to me?
Absolutely. The final delivery includes a fully commented Jupyter Notebook/Colab environment. In the Premium package, I use Explainable AI (SHAP values) to show you exactly which features drove the model's predictions.
3. Can you export the model so my developers can use it?
Yes! In the Premium tier, I serialize the optimized model using joblib or pickle (.pkl format), making it 100% ready for deployment into your web or mobile application.
4. What types of classification problems can you solve?
I handle Binary, Multi-class, and Multi-label classification. Common use cases include Customer Churn Prediction, Fraud Detection, Medical Diagnosis, and Spam Filtering.
