Canais - Practical Machine Learning with Python : :: Biblioteca ITESO

Registros relacionados: Practical Machine Learning with Python :

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Practical Machine Learning with Python : A Problem-Solver's Guide to Building Real-World Intelligent Systems /
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Mastering Machine Learning with Scikit-Learn : Apply Effective Learning Algorithms to Real-World Problems Using Scikit-Learn /
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Introduction to Machine Learning with Python : A Guide for Data Scientists /
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Python Machine Learning : Machine Learning and Deep Learning with Python, Scikit-Learn, and TensorFlow /
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Python Machine Learning : Unlock Deeper Insights into Machine Learning with this Vital Guide to Cutting-Edge Predictive Analytics /
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Machine Learning in Python : Essential Techniques for Predictive Analysis /
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Building Machine Learning Systems with Python : Get More from Your Data Through Creating Practical Machine Learning Systems with Python /
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Learning Scikit-Learn : Machine Learning in Python : Experience the Benefits of Machine Learning Techniques by Applying Them to Real-world Problems Using Python and the Open Source Scikit-Learn Library /
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Learn Keras for Deep Neural Networks : A Fast-Track Approach to Modern Deep Learning with Python /
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Artificial Intelligence Programming with Python : From Zero to Hero /
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Ensemble Machine Learning Cookbook : Over 35 Practical Recipes to Explore Ensemble Machine Learning Techniques Using Python /
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Scikit-Learn Cookbook : Over 50 Recipes to Incorporate Scikit-Learn into Every Step of the Data Science Pipeline, from Feature Extraction to Model Building and Model Evaluation /
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Machine Learning Algorithms : Popular Algorithms for Data Science and Machine Learning /
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Understanding Machine-Learning : From Theory to Algorithms /
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Understanding Machine-Learning : From Theory to Algorithms /
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Machine Learning with Spark : Create Scalable Machine Learning Applications to Power a Modern Data-Driven Business Using Spark /
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Deep Learning with Python /
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Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow : Concepts, Tools, and Techniques to Build Intelligent Systems /
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Python for Probability, Statistics, and Machine Learning /
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Tree-based Machine Learning Algorithms : Decision Trees, Random Forests, and Boosting /
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Neural Network Programming : How to Create Modern AI Systems with Python, TensorFlow, and Keras /
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Machine Learning with PyTorch and Scikit-Learn : Develop Machine Learning and Deep Learning Models with Python /
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An Introduction to Machine Learning /
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Machine Learning con PyTorch y Scikit-Learn : desarrollo de modelos Machine Learning y Deep Learning con Python /

Assunto: Algoritmos Computacionales

Assunto: Proceso de Datos - Tema Principal

Autor: Sarkar, Dipanjan

Autor: Bali, Raghav (autor)

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