3 projects for "matplotlib" with 2 filters applied:

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    Zero to Mastery Machine Learning

    Zero to Mastery Machine Learning

    All course materials for the Zero to Mastery Machine Learning

    ...The repository includes datasets, Jupyter notebooks, documentation, and example code that walk learners through the entire machine learning workflow from problem definition to model deployment. The course introduces essential tools such as NumPy, pandas, Matplotlib, and scikit-learn before moving on to deep learning with frameworks like TensorFlow and Keras. It also includes milestone projects that demonstrate how to build end-to-end machine learning systems using real datasets, including classification and regression tasks.
    Downloads: 1 This Week
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  • 2
    Python ML Jupyter Notebooks

    Python ML Jupyter Notebooks

    Practice and tutorial-style notebooks

    ...The project provides numerous examples and tutorials covering classical machine learning techniques such as regression, classification, clustering, and dimensionality reduction. It includes code implementations that show how to build models using popular libraries like scikit-learn, NumPy, pandas, and Matplotlib. The repository is designed to help learners understand both the theory and practical implementation of machine learning algorithms through step-by-step code examples. Many notebooks include explanations of algorithm behavior, data preparation techniques, and evaluation methods for machine learning models. The project also includes examples that demonstrate how to apply machine learning to real-world datasets and practical business problems.
    Downloads: 0 This Week
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  • 3
    AI Cheatsheets

    AI Cheatsheets

    Essential Cheat Sheets for deep learning and machine learning research

    ...The project aims to provide quick-reference materials that help engineers, researchers, and students review key techniques and frameworks without reading extensive documentation. It compiles cheat sheets for widely used libraries and technologies such as TensorFlow, Keras, NumPy, Pandas, Scikit-learn, Matplotlib, and PySpark. These materials summarize common functions, workflows, and best practices in a concise visual format that makes them easy to consult during development or study sessions. The repository functions as a centralized library where users can quickly access reference materials for both machine learning theory and practical programming tools. ...
    Downloads: 1 This Week
    Last Update:
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