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Hands-on Scikit-Learn for Machine Learning Applications
. Hands-on Scikit-Learn for Machine Learning Applications is an excellent starting point for those pursuing a career in machine learning. Students;
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Hands-On Machine Learning with scikit-learn and Scientific Python Toolkits
provide hands-on machine learning solutions with scikit-learn and Python toolkits. The book begins with an explanation of machine learning;
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Machine Learning with scikit-learn Quick Start Guide
-learn provides. This book teaches you how to use scikit-learn for machine learning. You will start by setting up and configuring your machine;
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Learning scikit-learn
learning and data-based methods to build intelligent applications and enhance your programming skills, this the book for you. No previous;
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Hands-on Machine Learning with Python
introduces tools such as NumPy for numerical processing, Pandas for panel data analysis, Matplotlib for visualization, Scikit-learn for machine;
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scikit-learn Cookbook -
Learn to use scikit-learn operations and functions for Machine Learning and deep learning applications. About This Book * Handle a;
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Hands-on Machine Learning with Python
introduces tools such as NumPy for numerical processing, Pandas for panel data analysis, Matplotlib for visualization, Scikit-learn for machine;
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Hands-On Machine Learning with Scikit-Learn and TensorFlow
scikit-learn to track an example machine-learning project end-to-end Explore several training models, including support vector machines, decision;
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Hands-on Machine Learning with Scikit-Learn, Keras, and TensorFlow
Scikit-Learn to track an example machine-learning project end-to-end Explore several training models, including support vector machines, decision;
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Machine Learning for OpenCV 4
unsupervised machine learning. You will gain hands-on experience using scikit-learn in Python for a variety of machine learning applications. Later;
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Mastering Machine Learning with scikit-learn -
Use scikit-learn to apply machine learning to real-world problems About This Book * Master popular machine learning models including;
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Machine Learning Fundamentals
With the flexibility and features of scikit-learn and Python, build machine learning algorithms that optimize the programming process and;
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Introduction to Machine Learning with Python
the steps necessary to create a successful machine-learning application with Python and the scikit-learn library. Authors Andreas Muller and;
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Machine Learning with Scikit-Learn and TensorFlow
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Python Machine Learning
latest additions to scikit-learn. It's also expanded to cover cutting-edge reinforcement learning techniques based on deep learning, as well as;
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Beginning Anomaly Detection Using Python-Based Deep Learning
statistical and traditional machine learning methods for anomaly detection using Scikit-Learn in Python, the book then provides an introduction to;
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Welding and Cutting Case Studies with Supervised Machine Learning
learning. Subsequently, it discusses supervised learning, highlighting Python libraries such as NumPy, Pandas and Scikit Learn programming. It also;
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Welding and Cutting Case Studies with Supervised Machine Learning
learning. Subsequently, it discusses supervised learning, highlighting Python libraries such as NumPy, Pandas and Scikit Learn programming. It also;
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Introduction to IoT with Machine Learning and Image Processing using Raspberry Pi
with Python Scikit-Learn library is explained to audience with an emphasis on supervised learning and classification. Image processing on IoT;
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Introduction to IoT with Machine Learning and Image Processing using Raspberry Pi
with Python Scikit-Learn library is explained to audience with an emphasis on supervised learning and classification. Image processing on IoT;
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Machine Learning for Finance
learning training courses for financial professionals. Rather than providing ready-made financial algorithms, the book focuses on the advanced ML;
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Data Science Projects with Python
Gain hands-on experience of Python programming with industry-standard machine learning techniques using pandas, scikit-learn, and XGBoost;
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Python Machine Learning Case Studies
learning concepts Work on real-world applications of machine learning Learn concepts of model selection and optimization Get a hands-on overview;
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Machine Learning Applications Using Python
Gain practical skills in machine learning for finance, healthcare, and retail. This book uses a hands-on approach by providing case studies;
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Machine Learning for iOS Developers
, into mobile devices, most of which can be used in multi-cloud settings. Focusing on Apple's ML services, Machine Learning for iOS Developers;
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Practical Machine Learning with Python
finance. For each case study, you will learn the application of various machine learning techniques and methods. The hands-on examples will help;
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Einde inhoud
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