9781617296819 - Machine Learning Bookcamp: Build a Portfolio of Real-Life Projects de Grigorev, Alexey (21 résultats)

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Paperback. Etat : New. The only way to learn is to practice! In   Machine Learning Bookcamp, you'll create and deploy Python-based machine learning models for a variety of increasingly challenging projects. Taking you from the basics of machine learning to complex applications such as image and text analysis, each new project builds on what you've learned in previous chapters. By the end of the bookcamp, you'll have built a portfolio of business-relevant machine learning projects that hiring managers will be excited to see. about the technologyMachine learning is an analysis technique for predicting trends and relationships based on historical data. As ML has matured as a discipline, an established set of algorithms has emerged for tackling a wide range of analysis tasks in business and research. By practicing the most important algorithms and techniques, you can quickly gain a footing in this important area. Luckily, that's exactly what you'll be doing in   Machine Learning Bookcamp. about the bookIn   Machine Learning Bookcamp  you'll learn the essentials of machine learning by completing a carefully designed set of real-world projects. Beginning as a novice, you'll start with the basic concepts of ML before tackling your first challenge: creating a car price predictor using linear regression algorithms. You'll then advance through increasingly difficult projects, developing your skills to build a churn prediction application, a flight delay calculator, an image classifier, and more. When you're done working through these fun and informative projects, you'll have a comprehensive machine learning skill set you can apply to practical on-the-job problems.   what's inside Code fundamental ML algorithms from scratchCollect and clean data for training modelsUse popular Python tools, including NumPy, Pandas, Scikit-Learn, and TensorFlowApply ML to complex datasets with images and textDeploy ML models to a production-ready environment about the readerFor readers with existing programming skills. No previous machine learning experience required. about the author Alexey Grigorev  has more than ten years of experience as a software engineer, and has spent the last six years focused on machine learning. Currently, he works as a lead data scientist at the OLX Group, where he deals with content moderation and image models. He is the author of two other books on using Java for data science and TensorFlow for deep learning.

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Paperback. Etat : new. Paperback. The only way to learn is to practice! In Machine Learning Bookcamp, youll create and deploy Python-based machine learning models for a variety of increasingly challenging projects. Taking you from the basics of machine learning to complex applications such as image and text analysis, each new project builds on what youve learned in previous chapters. By the end of the bookcamp, youll have built a portfolio of business-relevant machine learning projects that hiring managers will be excited to see. about the technologyMachine learning is an analysis technique for predicting trends and relationships based on historical data. As ML has matured as a discipline, an established set of algorithms has emerged for tackling a wide range of analysis tasks in business and research. By practicing the most important algorithms and techniques, you can quickly gain a footing in this important area. Luckily, thats exactly what youll be doing in Machine Learning Bookcamp. about the bookIn Machine Learning Bookcamp youll learn the essentials of machine learning by completing a carefully designed set of real-world projects. Beginning as a novice, youll start with the basic concepts of ML before tackling your first challenge: creating a car price predictor using linear regression algorithms. Youll then advance through increasingly difficult projects, developing your skills to build a churn prediction application, a flight delay calculator, an image classifier, and more. When youre done working through these fun and informative projects, youll have a comprehensive machine learning skill set you can apply to practical on-the-job problems. what's inside Code fundamental ML algorithms from scratchCollect and clean data for training modelsUse popular Python tools, including NumPy, Pandas, Scikit-Learn, and TensorFlowApply ML to complex datasets with images and textDeploy ML models to a production-ready environment about the readerFor readers with existing programming skills. No previous machine learning experience required. about the author Alexey Grigorev has more than ten years of experience as a software engineer, and has spent the last six years focused on machine learning. Currently, he works as a lead data scientist at the OLX Group, where he deals with content moderation and image models. He is the author of two other books on using Java for data science and TensorFlow for deep learning. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

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Paperback. Etat : New. The only way to learn is to practice! In   Machine Learning Bookcamp, you'll create and deploy Python-based machine learning models for a variety of increasingly challenging projects. Taking you from the basics of machine learning to complex applications such as image and text analysis, each new project builds on what you've learned in previous chapters. By the end of the bookcamp, you'll have built a portfolio of business-relevant machine learning projects that hiring managers will be excited to see. about the technologyMachine learning is an analysis technique for predicting trends and relationships based on historical data. As ML has matured as a discipline, an established set of algorithms has emerged for tackling a wide range of analysis tasks in business and research. By practicing the most important algorithms and techniques, you can quickly gain a footing in this important area. Luckily, that's exactly what you'll be doing in   Machine Learning Bookcamp. about the bookIn   Machine Learning Bookcamp  you'll learn the essentials of machine learning by completing a carefully designed set of real-world projects. Beginning as a novice, you'll start with the basic concepts of ML before tackling your first challenge: creating a car price predictor using linear regression algorithms. You'll then advance through increasingly difficult projects, developing your skills to build a churn prediction application, a flight delay calculator, an image classifier, and more. When you're done working through these fun and informative projects, you'll have a comprehensive machine learning skill set you can apply to practical on-the-job problems.   what's inside Code fundamental ML algorithms from scratchCollect and clean data for training modelsUse popular Python tools, including NumPy, Pandas, Scikit-Learn, and TensorFlowApply ML to complex datasets with images and textDeploy ML models to a production-ready environment about the readerFor readers with existing programming skills. No previous machine learning experience required. about the author Alexey Grigorev  has more than ten years of experience as a software engineer, and has spent the last six years focused on machine learning. Currently, he works as a lead data scientist at the OLX Group, where he deals with content moderation and image models. He is the author of two other books on using Java for data science and TensorFlow for deep learning.

Etat : New. &Uumlber den AutorAlexey Grigorev has more than ten years of experience as a software engineer, and has spent the last six years focused on machine learning. Currently, he works as a lead data scientist at the OLX Group, where he.

Paperback. Etat : new. Paperback. The only way to learn is to practice! In Machine Learning Bookcamp, youll create and deploy Python-based machine learning models for a variety of increasingly challenging projects. Taking you from the basics of machine learning to complex applications such as image and text analysis, each new project builds on what youve learned in previous chapters. By the end of the bookcamp, youll have built a portfolio of business-relevant machine learning projects that hiring managers will be excited to see. about the technologyMachine learning is an analysis technique for predicting trends and relationships based on historical data. As ML has matured as a discipline, an established set of algorithms has emerged for tackling a wide range of analysis tasks in business and research. By practicing the most important algorithms and techniques, you can quickly gain a footing in this important area. Luckily, thats exactly what youll be doing in Machine Learning Bookcamp. about the bookIn Machine Learning Bookcamp youll learn the essentials of machine learning by completing a carefully designed set of real-world projects. Beginning as a novice, youll start with the basic concepts of ML before tackling your first challenge: creating a car price predictor using linear regression algorithms. Youll then advance through increasingly difficult projects, developing your skills to build a churn prediction application, a flight delay calculator, an image classifier, and more. When youre done working through these fun and informative projects, youll have a comprehensive machine learning skill set you can apply to practical on-the-job problems. what's inside Code fundamental ML algorithms from scratchCollect and clean data for training modelsUse popular Python tools, including NumPy, Pandas, Scikit-Learn, and TensorFlowApply ML to complex datasets with images and textDeploy ML models to a production-ready environment about the readerFor readers with existing programming skills. No previous machine learning experience required. about the author Alexey Grigorev has more than ten years of experience as a software engineer, and has spent the last six years focused on machine learning. Currently, he works as a lead data scientist at the OLX Group, where he deals with content moderation and image models. He is the author of two other books on using Java for data science and TensorFlow for deep learning. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.