agoor97/Hands-on_Machine_Learning_Topics
This Repository provides some Notes and Tricks for using Scikit-Learn, Keras, and TensorFlow for Machine Learning, Deep Learning, and Application for Computer Vision and NLP.
This resource provides practical notes and tricks for applying machine learning and deep learning techniques, including computer vision and natural language processing. It takes theoretical concepts and shows how to implement them using popular tools like Scikit-learn, Keras, and TensorFlow. Data scientists, machine learning engineers, and researchers can use this to understand how to build, train, and optimize various AI models.
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Use this if you are a data scientist or AI practitioner looking for hands-on examples to implement machine learning and deep learning algorithms, from classification to deep computer vision.
Not ideal if you are a business user seeking a no-code solution or a complete, production-ready application rather than educational implementation guides.
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Jupyter Notebook
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MIT
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Last pushed
Sep 09, 2022
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