You will get Data cleaning & preprocessing, Visualizations, Model building, optimization
Project details
This project focuses on implementing regularized cost functions and gradient descent for both linear and logistic regression in Python. Regularization is a critical technique in machine learning to prevent overfitting by penalizing large coefficients, ensuring models generalize well to unseen data.
Machine Learning Tools
Keras, MATLAB, NumPy, OpenCV, pandas, Python, Python Scikit-Learn, SQL, TensorFlowWhat's included $7
These options are included with the project scope.
$7
- Delivery Time 3 days
- Number of Revisions 2
- Number of Model Variations 2
- Number of Scenarios 2
- Number of Graphs/Charts 4
- Model Validation/Testing
- Source Code
Optional add-ons
You can add these on the next page.
Fast 2 Days Delivery
+$3
Additional Revision
+$3
Additional Model Variation
(+ 1 Day)
+$3
Additional Scenario
(+ 1 Day)
+$2
Additional Graph/Chart
(+ 2 Days)
+$1About Kibirt
Machine Learning Freelancer
Addis Ababa, Ethiopia - 4:33 am local time
✔ Computer Vision: OpenCV, image processing, detecting objects, facial recognition.
✔ Data Science & Analytics: Clean, analyze, and visualize data to uncover insights using Python (Pandas, NumPy, Matplotlib)
✔ SQL & Databases: efficient queries to pull, shape, and optimize data for machine learning.
✔ Prompt Engineering & LLMs: fine-tune GPT models for specific needs.
Steps for completing your project
After purchasing the project, send requirements so Kibirt can start the project.
Delivery time starts when Kibirt receives requirements from you.
Kibirt works on your project following the steps below.
Revisions may occur after the delivery date.
gradient descent
Regularize cost function and run gradient descent.