SKU/Artículo: AMZ-B0FRN7RRKH

Machine Learning with Scikit-Learn, Keras, and TensorFlow: Train, Evaluate, and Deploy Models with Real-World Datasets, Code Walkthroughs, and Hands-On Projects Without Graphs

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Fuera de stock

Peso con empaque:
0.33 kg

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No

Condición
Nuevo

Producto de:
Amazon

Sobre este producto

Understand what machine learning is and why it matters today
Prepare data through cleaning, encoding, scaling, and feature selection
Train core models with Scikit-Learn for regression, classification, and clustering
Build deep learning models with Keras and TensorFlow step by step
Optimize models with hyperparameter tuning, regularization, and ensembles
Deploy models using Flask, FastAPI, Docker, and cloud services
Apply ML to real-world use cases including spam detection, credit risk prediction, image recognition, and time-series forecasting
Optimize performance for mobile and edge devices with TensorFlow Lite
Python programmers wanting to expand into ML and AI
Students building machine learning skills for academic or career growth
Data professionals moving from analytics into predictive modeling
Engineers and developers who want to deploy ML solutions in production environments
Focused on Scikit-Learn, Keras, and TensorFlow, the most popular ML libraries today
Covers the entire ML lifecycle: preprocessing, training, evaluation, optimization, deployment, and monitoring
Real-world datasets and portfolio-ready projects included
Hands-on exercises reinforce learning at every step

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Machine Learning with Scikit-Learn, Keras, and TensorFlow: Train, Evaluate, and Deploy Models with Real-World Datasets, Code Walkthroughs, and Hands-On Projects Without Graphs

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Machine Learning with Scikit-Learn, Keras, and TensorFlow: Train, Evaluate, and Deploy Models with Real-World Datasets, Code Walkthroughs, and Hands-On Projects Without Graphs

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