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This book provides an introduction to machine learning and cloud computing, both from a conceptual level, along with their usage with;
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Put the power of AWS Cloud machine learning services to work in your business and commercial applications! Machine Learning in the AWS;
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is a complete guide to help you become well versed with machine learning on the IBM Cloud using Python. Hands-On Machine Learning with IBM;
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present book tries to address IoT, Python and Machine Learning along with a small introduction to Image Processing. If you are a novice programmer;
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present book tries to address IoT, Python and Machine Learning along with a small introduction to Image Processing. If you are a novice programmer;
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Terraform. Learning how to interact and automate with Linux is essential for millions of professionals. Python makes it much easier. With this;
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New edition of the bestselling guide to artificial intelligence with Python, updated to Python 3.x, with seven new chapters that cover RNNs;
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recommendation systems. With Building Machine Learning Systems with Python, you'll gain the tools and understanding required to build your own systems;
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decreasing at the same time, there is no better time to learn machine learning using Python. Machine learning tasks that once required enormous;
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in Python. This book starts with an introduction to geodata and covers topics such as GIS and common tools, standard formats of geographical data;
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development and machine learning. This book will help developers working with machine learning and Python to put their knowledge to work and create;
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regular IDE. You'll start by learning how to use Jupyter Notebooks to improve the way you program with Python. After getting a good grounding;
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Learning with Python introduces you to the theory behind reinforcement learning (RL) algorithms and the code that will be used to implement them;
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world of Machine Learning with Python?If your answer is YES, then youve come to the right source.Whether you want to start;
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DescriptionPython Machine Learning, Third Edition is a comprehensive guide to machine learning and deep learning with Python. It acts as both a step-by-step;
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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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language processing, and computer vision in the cloud environment. Generic design patterns in Python programming is clearly explained, emphasizing;
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language processing, and computer vision in the cloud environment. Generic design patterns in Python programming is clearly explained, emphasizing;
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Unlock modern machine learning and deep learning techniques with Python by using the latest cutting-edge open source Python libraries;
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Deep Learning for Complete Beginners: A Python-Based Introduction is for complete beginners in machine learning. It introduces fundamental;
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entry point to machine learning. This book starts with an introduction to machine learning and the Python language and shows you how to;
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This practical guide shows intermediate and advanced web and mobile app developers how to build highly scalable Python applications in the;
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models using Azure and end-to-end ML pipelines on the cloud. The book starts with an overview of an end-to-end ML project and a guide on how to;
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Inside this book you will find all the basic notions to start with Python and all the programming concepts to build machine learning;
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ML and AI services that are easy to implement in the cloud. Hands-On Machine Learning with Azure teaches you how to perform advanced ML;
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