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  2. Learn how to complete a machine learning project in Python from scratch, using the iris dataset. Follow the step-by-step tutorial to install Python and SciPy, load, summarize, visualize and evaluate data, and make predictions.

  3. scikit-learn is an open source library for predictive data analysis with various algorithms and tools. Learn how to use scikit-learn for classification, regression, clustering, dimensionality reduction, model selection and preprocessing.

    • Step 1: Install Python and Required Libraries
    • Step 2: Choose An Integrated Development Environment
    • Step 3: Load Datasets

    Begin by installing Python on your system. You can download the latest version from the official Python website. Additionally, you’ll need to install the required libraries for machine learning, like NumPy, Pandas, Matplotlib, and Scikit-learn.

    Select an IDE for writing and executing your Python code. Some popular options include Jupyter Notebook, PyCharm, and Visual Studio Code.

    For machine learning projects, you’ll often work with datasets. Python’s Pandas library allows you to load and manipulate data efficiently.

    • 62 min
  4. Learn how to make computers learn from data and statistics using Python modules. This tutorial covers data sets, data types, and basic machine learning concepts.

    • Embeddings and Vector Databases With ChromaDB. Nov 15, 2023 advanced databases data-science machine-learning.
    • Using k-Nearest Neighbors (kNN) in Python. May 23, 2023 data-science intermediate machine-learning.
    • Build Your Own Face Recognition Tool With Python. Apr 24, 2023 intermediate machine-learning.
    • Linear Regression in Python. data-science intermediate machine-learning.
  5. Dive into Machine Learning with Python! This IBM course on Coursera covers supervised vs unsupervised learning, classification algorithms, clustering, and hands-on labs using SciPy and scikit-learn. Gain job-ready skills and earn a certificate in Machine Learning.

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  7. Apr 14, 2023 · Learn how to use scikit-learn, an open-source Python library for machine learning, with this hands-on tutorial. Explore data, data preprocessing, model training, and model evaluation with the wine dataset.

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