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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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Real-World Machine Learning
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Real-World Machine Learning
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Machine learning and AI for healthcare : Big data for improved health outcomes
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Outlier Analysis
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Deep learning with Azure : building and deploying artificial intelligence solutions on the Microsoft AI platform
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Introduction to deep learning
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Introduction to deep learning using R : a step-by-step guide to learning and implementing deep learning models using R
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Machine learning for text
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Machine Learning with PySpark : With Natural Language Processing and Recommender Systems
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Deep learning with applications using Python : chatbots and face, object, and speech recognition with TensorFlow and Keras
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Machine learning design patterns : solutions to common challenges in data preparation, model building, and MLOps
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Machine learning and security : protecting systems with data and algorithms
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Machine learning for financial risk management with Python : algorithms for modeling risk
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Building machine learning powered applications : going from idea to product
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Reinforcement learning : industrial applications of intelligent agents
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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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Practical time series analysis : prediction with statistics and machine learning
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Building machine learning pipelines : automating model life cycles with TensorFlow
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Blueprints for text analysis using Python : machine learning-based solutions for common real world (NLP) applications
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Machine Learning and Data Science Blueprints for Finance : from building trading strategies to Robo-Advisors using Python
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Deep Learning from Scratch : Building with Python from first principles
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Deep Learning Cookbook : Practical recipes to get started quickly
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Introduction to Machine Learning with R : Rigorous Mathematical Modeling