You will get End-to-End ML Pipeline using Python: Data Cleaning to Model Optimization


Project details
I deliver a complete, end-to-end machine learning pipeline—from raw data cleaning to advanced model fine-tuning. What sets this project apart is the focus on customized solutions, high-quality preprocessing, and performance-driven model optimization, tailored specifically to each client’s data and goals. Whether you're starting from scratch or refining an existing model, I provide clear insights, clean code, and reliable results.
Machine Learning Tools
Apache Spark, Keras, NumPy, OpenCV, pandas, Python, Python Scikit-Learn, PyTorch, scikit-learn, TensorFlowWhat's included
| Service Tiers |
Starter
$80
|
Standard
$120
|
Advanced
$150
|
|---|---|---|---|
| Delivery Time | 5 days | 6 days | 8 days |
Number of Revisions | 1 | 2 | 3 |
Number of Model Variations | 2 | 3 | 5 |
Number of Scenarios | 1 | 2 | 3 |
Number of Graphs/Charts | 2 | 3 | 5 |
Model Validation/Testing | |||
Model Documentation | |||
Data Source Connectivity | |||
Source Code |
Frequently asked questions
About Akalu
AI Engineer | Data Engineer | Python Developer | Math Instructor|
Addis Ababa, Ethiopia - 11:54 pm local time
I can help you with the following activities:
- Data Engineering and analysis Python, Apache Spark, Hadoop, Hive
- Data visualization using Tableau and Power-BI.
- Dataset preprocessing using Python, Pyspark
- Image data annotation to train machine learning models.
- Developing deep learning-based AI tools using Python.
- Companies or personal project portfolio preparation
- Tutoring/ teaching mathematics courses.
- Presentation slide using Canva,
- Flyers design, Poster, and Resume design.
- Working with Microsoft Excel and Microsoft Word
Steps for completing your project
After purchasing the project, send requirements so Akalu can start the project.
Delivery time starts when Akalu receives requirements from you.
Akalu works on your project following the steps below.
Revisions may occur after the delivery date.
1
Project requirements are reviewed, and any clarifications are requested.
1
Data is cleaned, preprocessed, and prepared for modeling.







