daniel spacagna (38 résultats)

Etat : very_good. Gently read. May have name of previous ownership, or ex-library edition. Binding tight; spine straight and smooth, with no creasing; covers clean and crisp. Minimal signs of handling or shelving. 100% GUARANTEE! Shipped with delivery confirmation, if you're not satisfied with purchase please return item! Ships USPS Media Mail.

Paperback. Etat : Very Good. No Jacket. May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less.

Etat : Good. Item in good condition. Textbooks may not include supplemental items i.e. CDs, access codes etc.

Etat : New.

Etat : New.

Etat : New.

Etat : New.

Etat : As New. Unread book in perfect condition.

Etat : As New. Unread book in perfect condition.

Digital. Etat : New. Take your machine learning skills to the next level by mastering Deep Learning concepts and algorithms using Python.About This Book. Explore and create intelligent systems using cutting-edge deep learning techniques. Implement deep learning algorithms and work with revolutionary libraries in Python. Get real-world examples and easy-to-follow tutorials on Theano, TensorFlow, H2O and moreWho This Book Is ForThis book is for Data Science practitioners as well as aspirants who have a basic foundational understanding of Machine Learning concepts and some programming experience with Python. A mathematical background with a conceptual understanding of calculus and statistics is also desired.What You Will Learn. Get a practical deep dive into deep learning algorithms. Explore deep learning further with Theano, Caffe, Keras, and TensorFlow. Learn about two of the most powerful techniques at the core of many practical deep learning implementations: Auto-Encoders and Restricted Boltzmann Machines. Dive into Deep Belief Nets and Deep Neural Networks. Discover more deep learning algorithms with Dropout and Convolutional Neural Networks. Get to know device strategies so you can use deep learning algorithms and libraries in the real worldIn DetailWith an increasing interest in AI around the world, deep learning has attracted a great deal of public attention. Every day, deep learning algorithms are used broadly across different industries.The book will give you all the practical information available on the subject, including the best practices, using real-world use cases. You will learn to recognize and extract information to increase predictive accuracy and optimize results.Starting with a quick recap of important machine learning concepts, the book will delve straight into deep learning principles using Sci-kit learn. Moving ahead, you will learn to use the latest open source libraries such as Theano, Keras, Google's TensorFlow, and H20. Use this guide to uncover the difficulties of pattern recognition, scaling data with greater accuracy and discussing deep learning algorithms and techniques.Whether you want to dive deeper into Deep Learning, or want to investigate how to get more out of this powerful technology, you'll find everything inside.Style and approachPython Machine Learning by example follows practical hands on approach. It walks you through the key elements of Python and its powerful machine learning libraries with the help of real world projects.

Paperback. Etat : New. 2nd Revised edition. The book will help you learn deep neural networks and their applications in computer vision, generative models, and natural language processing. It will also introduce you to the area of reinforcement learning, where you'll learn the state-of-the-art algorithms to teach the machines how to play games like Go and Atari.

Etat : New.

Etat : New.

Etat : New. In.

Etat : New. In English.

Etat : New. pp. 406.

Paperback. Etat : New.

paperback. Etat : New.

Digital. Etat : New. Take your machine learning skills to the next level by mastering Deep Learning concepts and algorithms using Python.About This Book. Explore and create intelligent systems using cutting-edge deep learning techniques. Implement deep learning algorithms and work with revolutionary libraries in Python. Get real-world examples and easy-to-follow tutorials on Theano, TensorFlow, H2O and moreWho This Book Is ForThis book is for Data Science practitioners as well as aspirants who have a basic foundational understanding of Machine Learning concepts and some programming experience with Python. A mathematical background with a conceptual understanding of calculus and statistics is also desired.What You Will Learn. Get a practical deep dive into deep learning algorithms. Explore deep learning further with Theano, Caffe, Keras, and TensorFlow. Learn about two of the most powerful techniques at the core of many practical deep learning implementations: Auto-Encoders and Restricted Boltzmann Machines. Dive into Deep Belief Nets and Deep Neural Networks. Discover more deep learning algorithms with Dropout and Convolutional Neural Networks. Get to know device strategies so you can use deep learning algorithms and libraries in the real worldIn DetailWith an increasing interest in AI around the world, deep learning has attracted a great deal of public attention. Every day, deep learning algorithms are used broadly across different industries.The book will give you all the practical information available on the subject, including the best practices, using real-world use cases. You will learn to recognize and extract information to increase predictive accuracy and optimize results.Starting with a quick recap of important machine learning concepts, the book will delve straight into deep learning principles using Sci-kit learn. Moving ahead, you will learn to use the latest open source libraries such as Theano, Keras, Google's TensorFlow, and H20. Use this guide to uncover the difficulties of pattern recognition, scaling data with greater accuracy and discussing deep learning algorithms and techniques.Whether you want to dive deeper into Deep Learning, or want to investigate how to get more out of this powerful technology, you'll find everything inside.Style and approachPython Machine Learning by example follows practical hands on approach. It walks you through the key elements of Python and its powerful machine learning libraries with the help of real world projects.

Etat : New.

Etat : New.

Etat : As New. Unread book in perfect condition.

Etat : As New. Unread book in perfect condition.

Taschenbuch. Etat : Neu. Neuware - This is your ultimate tool to change your life! IMAGINE YOU HAD A ROAD MAP, a step-by-step guide to help you get from pain, loss and disappointment to passion, purpose and success Your pain, trials and disappointments will actually become the fuel that powers your destiny. You just need the GPS directions and the turn by turn guidance that Dan Spacagna describes in 5 Keys-How to go from Stress to Success. In 5 easy to apply steps you will be able to \* lower your mental and physical stress \* overcome fears \* break through past limiting beliefs \* move quickly towards your purpose Dan will show you how he overcame, divorce, living on government assistance, suffering through a two-year clinical depression and eating disorder, being prescribed drugs for the rest of his life to having success traveling the world teaching life-changing skills to tens of thousands. Dan takes thousands of hours of study and dozens of psychology and personal development books and removes the complicated language and the stuff that doesn't work. What's left is the 5 Keys to unlocking your purpose, reaching fulfillment and changing your life.

Digital. Etat : New. Take your machine learning skills to the next level by mastering Deep Learning concepts and algorithms using Python.About This Book. Explore and create intelligent systems using cutting-edge deep learning techniques. Implement deep learning algorithms and work with revolutionary libraries in Python. Get real-world examples and easy-to-follow tutorials on Theano, TensorFlow, H2O and moreWho This Book Is ForThis book is for Data Science practitioners as well as aspirants who have a basic foundational understanding of Machine Learning concepts and some programming experience with Python. A mathematical background with a conceptual understanding of calculus and statistics is also desired.What You Will Learn. Get a practical deep dive into deep learning algorithms. Explore deep learning further with Theano, Caffe, Keras, and TensorFlow. Learn about two of the most powerful techniques at the core of many practical deep learning implementations: Auto-Encoders and Restricted Boltzmann Machines. Dive into Deep Belief Nets and Deep Neural Networks. Discover more deep learning algorithms with Dropout and Convolutional Neural Networks. Get to know device strategies so you can use deep learning algorithms and libraries in the real worldIn DetailWith an increasing interest in AI around the world, deep learning has attracted a great deal of public attention. Every day, deep learning algorithms are used broadly across different industries.The book will give you all the practical information available on the subject, including the best practices, using real-world use cases. You will learn to recognize and extract information to increase predictive accuracy and optimize results.Starting with a quick recap of important machine learning concepts, the book will delve straight into deep learning principles using Sci-kit learn. Moving ahead, you will learn to use the latest open source libraries such as Theano, Keras, Google's TensorFlow, and H20. Use this guide to uncover the difficulties of pattern recognition, scaling data with greater accuracy and discussing deep learning algorithms and techniques.Whether you want to dive deeper into Deep Learning, or want to investigate how to get more out of this powerful technology, you'll find everything inside.Style and approachPython Machine Learning by example follows practical hands on approach. It walks you through the key elements of Python and its powerful machine learning libraries with the help of real world projects.

Paperback. Etat : New. New. book.

Paperback. Etat : New. 2nd Revised edition. The book will help you learn deep neural networks and their applications in computer vision, generative models, and natural language processing. It will also introduce you to the area of reinforcement learning, where you'll learn the state-of-the-art algorithms to teach the machines how to play games like Go and Atari.

Digital. Etat : New. Take your machine learning skills to the next level by mastering Deep Learning concepts and algorithms using Python.About This Book. Explore and create intelligent systems using cutting-edge deep learning techniques. Implement deep learning algorithms and work with revolutionary libraries in Python. Get real-world examples and easy-to-follow tutorials on Theano, TensorFlow, H2O and moreWho This Book Is ForThis book is for Data Science practitioners as well as aspirants who have a basic foundational understanding of Machine Learning concepts and some programming experience with Python. A mathematical background with a conceptual understanding of calculus and statistics is also desired.What You Will Learn. Get a practical deep dive into deep learning algorithms. Explore deep learning further with Theano, Caffe, Keras, and TensorFlow. Learn about two of the most powerful techniques at the core of many practical deep learning implementations: Auto-Encoders and Restricted Boltzmann Machines. Dive into Deep Belief Nets and Deep Neural Networks. Discover more deep learning algorithms with Dropout and Convolutional Neural Networks. Get to know device strategies so you can use deep learning algorithms and libraries in the real worldIn DetailWith an increasing interest in AI around the world, deep learning has attracted a great deal of public attention. Every day, deep learning algorithms are used broadly across different industries.The book will give you all the practical information available on the subject, including the best practices, using real-world use cases. You will learn to recognize and extract information to increase predictive accuracy and optimize results.Starting with a quick recap of important machine learning concepts, the book will delve straight into deep learning principles using Sci-kit learn. Moving ahead, you will learn to use the latest open source libraries such as Theano, Keras, Google's TensorFlow, and H20. Use this guide to uncover the difficulties of pattern recognition, scaling data with greater accuracy and discussing deep learning algorithms and techniques.Whether you want to dive deeper into Deep Learning, or want to investigate how to get more out of this powerful technology, you'll find everything inside.Style and approachPython Machine Learning by example follows practical hands on approach. It walks you through the key elements of Python and its powerful machine learning libraries with the help of real world projects.

Paperback / softback. Etat : New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.

Paperback. Etat : New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.