Machine Learning Model Training & EvaluationHassan Razzaq
Machine Learning Model Training & Evaluation
Need help turning your dataset into a working machine learning model?
I will build a clean and practical machine learning pipeline using Python and industry-standard ML libraries.
What I can help with
• Data cleaning and preprocessing
• Missing-value handling
• Categorical data encoding
• Feature engineering
• Exploratory data analysis
• Train/test splitting
• Machine learning model training
• Model comparison
• Hyperparameter tuning
• Model evaluation
• Performance analysis
• Model saving and documentation
Models I can work with
• Linear Regression
• Logistic Regression
• Decision Trees
• Random Forest
• K-Nearest Neighbors (KNN)
• Support Vector Machines (SVM)
• Gradient Boosting / AdaBoost
• Other suitable Scikit-learn models depending on your dataset and problem
What you will receive
✓ Clean and organized Python code
✓ Jupyter Notebook
✓ Trained machine learning model
✓ Model evaluation results
✓ Comparison of suitable algorithms
✓ Saved model file when required
✓ Clear explanation of the approach and results
I focus on practical, understandable machine learning solutions rather than simply training a model and giving you an accuracy score.
Send me your dataset and project requirements, and I will recommend the appropriate approach.
Starting at$30
Duration3 days
Tags
Model Evaluation
Predictive Modeling
Python
Regression
scikit-learn
Data Scientist
Deep learning
Machine learning
Model Training
Service provided by
Hassan Razzaq Rawalpindi, Pakistan
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- Followers
Machine Learning Model Training & EvaluationHassan Razzaq
Starting at$30
Duration3 days
Tags
Model Evaluation
Predictive Modeling
Python
Regression
scikit-learn
Data Scientist
Deep learning
Machine learning
Model Training
Machine Learning Model Training & Evaluation
Need help turning your dataset into a working machine learning model?
I will build a clean and practical machine learning pipeline using Python and industry-standard ML libraries.
What I can help with
• Data cleaning and preprocessing
• Missing-value handling
• Categorical data encoding
• Feature engineering
• Exploratory data analysis
• Train/test splitting
• Machine learning model training
• Model comparison
• Hyperparameter tuning
• Model evaluation
• Performance analysis
• Model saving and documentation
Models I can work with
• Linear Regression
• Logistic Regression
• Decision Trees
• Random Forest
• K-Nearest Neighbors (KNN)
• Support Vector Machines (SVM)
• Gradient Boosting / AdaBoost
• Other suitable Scikit-learn models depending on your dataset and problem
What you will receive
✓ Clean and organized Python code
✓ Jupyter Notebook
✓ Trained machine learning model
✓ Model evaluation results
✓ Comparison of suitable algorithms
✓ Saved model file when required
✓ Clear explanation of the approach and results
I focus on practical, understandable machine learning solutions rather than simply training a model and giving you an accuracy score.
Send me your dataset and project requirements, and I will recommend the appropriate approach.
$30