https://github.com/kevinndungu-source/machine_learning

Machine Learning - This is a hands-on Machine Learning endeavor showcasing data preprocessing, feature engineering, and model deployment using Amazon SageMaker, aimed at advancing proficiency in ML workflows.
https://github.com/kevinndungu-source/machine_learning

data-manipulation feature-engineering feature-extraction imputation-methods python regression-models supervised-machine-learning

Last synced: about 2 months ago
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Machine Learning - This is a hands-on Machine Learning endeavor showcasing data preprocessing, feature engineering, and model deployment using Amazon SageMaker, aimed at advancing proficiency in ML workflows.

• Host: GitHub
• URL: https://github.com/kevinndungu-source/machine_learning
• Owner: kevinndungu-source
• License: mit
• Created: 2024-03-23T11:16:34.000Z (about 1 year ago)
• Default Branch: main
• Last Pushed: 2024-06-19T16:24:59.000Z (11 months ago)
• Last Synced: 2025-01-16T23:43:27.497Z (4 months ago)
• Topics: data-manipulation, feature-engineering, feature-extraction, imputation-methods, python, regression-models, supervised-machine-learning
• Language: Jupyter Notebook
• Homepage:
• Size: 126 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Machine Learning Code

Welcome to my Machine Learning (ML) repository! This collection of code files serves as a comprehensive resource for mastering various aspects of the ML workflow. From fetching data from scikit-learn datasets to advanced tasks like feature engineering and model deployment using Amazon SageMaker, this repository covers it all.

Technologies Used:

- Amazon SageMaker: Utilized for running Jupyter notebooks, managing training jobs, and deploying models.

- Python: Programming language used extensively for ML model development and scripting.

- scikit-learn: Essential library for data preprocessing, feature extraction, and model training.

- Pandas: Used for data manipulation and analysis.

- NumPy: Fundamental library for numerical operations and array processing in Python.

- Matplotlib and Seaborn: Libraries for data visualization and exploratory data analysis (EDA).

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![Sagemaker](https://github.com/kevinndungu-source/Machine_Learning/assets/114335263/04040e20-c999-49cc-b9dd-bb24d544e3e6)

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Whether you're new to ML or looking to expand your expertise, these code examples provide hands-on experience and practical insights into building and deploying ML models effectively with Amazon SageMaker.

Feel free to explore the code, experiment with different techniques, and elevate your ML skills with this repository!

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