Hearty john (46 resultados)

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

Paperback. Condición: Very Good. Solve challenging data science problems by mastering cutting-edge machine learning techniques in Python About This Book ? Resolve complex machine learning problems and explore deep learning ? Learn to use Python code for implementing a range of machine learning algorithms and techniques ? A practical tutorial that tackles real-world computing problems through a rigorous and effective approach Who This Book Is For This title is for Python developers and analysts or data scientists who are looking to add to their existing skills by accessing some of the most powerful recent trends in data science. If you've ever considered building your own image or text-tagging solution, or of entering a Kaggle contest for instance, this book is for you! Prior experience of Python and grounding in some of the core concepts of machine learning would be helpful. What You Will Learn ? Compete with top data scientists by gaining a practical and theoretical understanding of cutting-edge deep learning algorithms ? Apply your new found skills to solve real problems, through clearly-explained code for every technique and test ? Automate large sets of complex data and overcome time-consuming practical challenges ? Improve the accuracy of models and your existing input data using powerful feature engineering techniques ? Use multiple learning techniques together to improve the consistency of results ? Understand the hidden structure of datasets using a range of unsupervised techniques ? Gain insight into how the experts solve challenging data problems with an effective, iterative, and validation-focused approach ? Improve the effectiveness of your deep learning models further by using powerful ensembling techniques to strap multiple models together In Detail Designed to take you on a guided tour of the most relevant and powerful machine learning techniques in use today by top data scientists, this book is just what you need to push your Python algorithms to maximum potential. Clear examples and detailed code samples demonstrate deep learning techniques, semi-supervised learning, and more - all whilst working with real-world applications that include image, music, text, and financial data. The machine learning techniques covered in this book are at the forefront of commercial practice. They are applicable now for the first time in contexts such as image recognition, NLP and web search, computational creativity, and commercial/financial data modeling. Deep Learning algorithms and ensembles of models are in use by data scientists at top tech and digital companies, but the skills needed to apply them successfully, while in high demand, are still scarce. This book is designed to take the reader on a guided tour of the most relevant and powerful machine learning techniques. Clear descriptions of how techniques work and detailed code examples demonstrate deep learning techniques, semi-supervised learning and more, in real world applications. We will also learn about NumPy and Theano. By this end of this book, you will learn a set of advanced Machine Learning techniques and acquire a broad set of powerful skills in the area of feature selection & feature engineering. Style and approach This book focuses on clarifying the theory and code behind complex algorithms to make them practical, useable, and well-understood. Each topic is described with real-world applications, providing both broad contextual coverage and detailed guidance.…

Paperback. Condición: Very Good. Solve challenging data science problems by mastering cutting-edge machine learning techniques in Python About This Book ? Resolve complex machine learning problems and explore deep learning ? Learn to use Python code for implementing a range of machine learning algorithms and techniques ? A practical tutorial that tackles real-world computing problems through a rigorous and effective approach Who This Book Is For This title is for Python developers and analysts or data scientists who are looking to add to their existing skills by accessing some of the most powerful recent trends in data science. If you've ever considered building your own image or text-tagging solution, or of entering a Kaggle contest for instance, this book is for you! Prior experience of Python and grounding in some of the core concepts of machine learning would be helpful. What You Will Learn ? Compete with top data scientists by gaining a practical and theoretical understanding of cutting-edge deep learning algorithms ? Apply your new found skills to solve real problems, through clearly-explained code for every technique and test ? Automate large sets of complex data and overcome time-consuming practical challenges ? Improve the accuracy of models and your existing input data using powerful feature engineering techniques ? Use multiple learning techniques together to improve the consistency of results ? Understand the hidden structure of datasets using a range of unsupervised techniques ? Gain insight into how the experts solve challenging data problems with an effective, iterative, and validation-focused approach ? Improve the effectiveness of your deep learning models further by using powerful ensembling techniques to strap multiple models together In Detail Designed to take you on a guided tour of the most relevant and powerful machine learning techniques in use today by top data scientists, this book is just what you need to push your Python algorithms to maximum potential. Clear examples and detailed code samples demonstrate deep learning techniques, semi-supervised learning, and more - all whilst working with real-world applications that include image, music, text, and financial data. The machine learning techniques covered in this book are at the forefront of commercial practice. They are applicable now for the first time in contexts such as image recognition, NLP and web search, computational creativity, and commercial/financial data modeling. Deep Learning algorithms and ensembles of models are in use by data scientists at top tech and digital companies, but the skills needed to apply them successfully, while in high demand, are still scarce. This book is designed to take the reader on a guided tour of the most relevant and powerful machine learning techniques. Clear descriptions of how techniques work and detailed code examples demonstrate deep learning techniques, semi-supervised learning and more, in real world applications. We will also learn about NumPy and Theano. By this end of this book, you will learn a set of advanced Machine Learning techniques and acquire a broad set of powerful skills in the area of feature selection & feature engineering. Style and approach This book focuses on clarifying the theory and code behind complex algorithms to make them practical, useable, and well-understood. Each topic is described with real-world applications, providing both broad contextual coverage and detailed guidance.…

Pamphlet. Condición: Very Good. Vol 33, pp. 1-17, Map, Photo, Extracted from orig vol, begins with title page, Stapled & trimmed, thus is llike a pamphlet, last page in facsimile else VG.

Paperback. Condición: Very Good. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.

Condición: New.

Paperback. Condición: New. Solve challenging data science problems by mastering cutting-edge machine learning techniques in PythonAbout This Book. Resolve complex machine learning problems and explore deep learning. Learn to use Python code for implementing a range of machine learning algorithms and techniques. A practical tutorial that tackles real-world computing problems through a rigorous and effective approachWho This Book Is ForThis title is for Python developers and analysts or data scientists who are looking to add to their existing skills by accessing some of the most powerful recent trends in data science. If you've ever considered building your own image or text-tagging solution, or of entering a Kaggle contest for instance, this book is for you!Prior experience of Python and grounding in some of the core concepts of machine learning would be helpful.What You Will Learn. Compete with top data scientists by gaining a practical and theoretical understanding of cutting-edge deep learning algorithms. Apply your new found skills to solve real problems, through clearly-explained code for every technique and test. Automate large sets of complex data and overcome time-consuming practical challenges. Improve the accuracy of models and your existing input data using powerful feature engineering techniques. Use multiple learning techniques together to improve the consistency of results. Understand the hidden structure of datasets using a range of unsupervised techniques. Gain insight into how the experts solve challenging data problems with an effective, iterative, and validation-focused approach. Improve the effectiveness of your deep learning models further by using powerful ensembling techniques to strap multiple models togetherIn DetailDesigned to take you on a guided tour of the most relevant and powerful machine learning techniques in use today by top data scientists, this book is just what you need to push your Python algorithms to maximum potential. Clear examples and detailed code samples demonstrate deep learning techniques, semi-supervised learning, and more - all whilst working with real-world applications that include image, music, text, and financial data.The machine learning techniques covered in this book are at the forefront of commercial practice. They are applicable now for the first time in contexts such as image recognition, NLP and web search, computational creativity, and commercial/financial data modeling. Deep Learning algorithms and ensembles of models are in use by data scientists at top tech and digital companies, but the skills needed to apply them successfully, while in high demand, are still scarce.This book is designed to take the reader on a guided tour of the most relevant and powerful machine learning techniques. Clear descriptions of how techniques work and detailed code examples demonstrate deep learning techniques, semi-supervised learning and more, in real world applications. We will also learn about NumPy and Theano.By this end of th.…

Condición: New. pp. 278.

Condición: As New. Unread book in perfect condition.

Condición: As New. Unread book in perfect condition.

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Condición: As New. Unread book in perfect condition.

Condición: As New. Unread book in perfect condition.

Condición: New. pp. 916.

Digital. Condición: New. No detailed description available for "Python: Real World Machine Learning".

Paperback. Condición: New. Solve challenging data science problems by mastering cutting-edge machine learning techniques in PythonAbout This Book. Resolve complex machine learning problems and explore deep learning. Learn to use Python code for implementing a range of machine learning algorithms and techniques. A practical tutorial that tackles real-world computing problems through a rigorous and effective approachWho This Book Is ForThis title is for Python developers and analysts or data scientists who are looking to add to their existing skills by accessing some of the most powerful recent trends in data science. If you've ever considered building your own image or text-tagging solution, or of entering a Kaggle contest for instance, this book is for you!Prior experience of Python and grounding in some of the core concepts of machine learning would be helpful.What You Will Learn. Compete with top data scientists by gaining a practical and theoretical understanding of cutting-edge deep learning algorithms. Apply your new found skills to solve real problems, through clearly-explained code for every technique and test. Automate large sets of complex data and overcome time-consuming practical challenges. Improve the accuracy of models and your existing input data using powerful feature engineering techniques. Use multiple learning techniques together to improve the consistency of results. Understand the hidden structure of datasets using a range of unsupervised techniques. Gain insight into how the experts solve challenging data problems with an effective, iterative, and validation-focused approach. Improve the effectiveness of your deep learning models further by using powerful ensembling techniques to strap multiple models togetherIn DetailDesigned to take you on a guided tour of the most relevant and powerful machine learning techniques in use today by top data scientists, this book is just what you need to push your Python algorithms to maximum potential. Clear examples and detailed code samples demonstrate deep learning techniques, semi-supervised learning, and more - all whilst working with real-world applications that include image, music, text, and financial data.The machine learning techniques covered in this book are at the forefront of commercial practice. They are applicable now for the first time in contexts such as image recognition, NLP and web search, computational creativity, and commercial/financial data modeling. Deep Learning algorithms and ensembles of models are in use by data scientists at top tech and digital companies, but the skills needed to apply them successfully, while in high demand, are still scarce.This book is designed to take the reader on a guided tour of the most relevant and powerful machine learning techniques. Clear descriptions of how techniques work and detailed code examples demonstrate deep learning techniques, semi-supervised learning and more, in real world applications. We will also learn about NumPy and Theano.By this end of th.…

Condición: Sehr gut. Zustand: Sehr gut | Seiten: 956 | Sprache: Englisch | Produktart: Bücher | Explore the great features of the all-new JIRA 7 to manage projects and effectively handle bugs and software issues Key Features Updated for JIRA 7, this book covers all the new features introduced in JIRA 7 with a dedicated chapter on JIRA Service Desk-one of the biggest new add-ons to JIRA This book lays a strong foundation to work with agile projects in JIRA from both the administrator and end user's perspective Learn to solve challenging data science problems by building powerful machine learning models using Python Book Description Machine learning is increasingly spreading in the modern data-driven world. It is used extensively across many fields such as search engines, robotics, self-driving cars, and more. Machine learning is transforming the way we understand and interact with the world around us. In the first module, Python Machine Learning Cookbook, you will learn how to perform various machine learning tasks using a wide variety of machine learning algorithms to solve real-world problems and use Python to implement these algorithms. The second module, Advanced Machine Learning with Python, is designed to take you on a guided tour of the most relevant and powerful machine learning techniques and you'll acquire a broad set of powerful skills in the area of feature selection and feature engineering. The third module in this learning path, Large Scale Machine Learning with Python, dives into scalable machine learning and the three forms of scalability. It covers the most effective machine learning techniques on a map reduce framework in Hadoop and Spark in Python. This Learning Path will teach you Python machine learning for the real world. The machine learning techniques covered in this Learning Path are at the forefront of commercial practice. This Learning Path combines some of the best that Packt has to offer in one complete, curated package. It includes content from the following Packt products: Python Machine Learning Cookbook by Prateek Joshi Advanced Machine Learning with Python by John Hearty Large Scale Machine Learning with Python by Bastiaan Sjardin, Alberto Boschetti, Luca Massaron What you will learn Use predictive modeling and apply it to real-world problems Understand how to perform market segmentation using unsupervised learning Apply your new-found skills to solve real problems, through clearly-explained code for every technique and test Compete with top data scientists by gaining a practical and theoretical understanding of cutting-edge deep learning algorithms Increase predictive accuracy with deep learning and scalable data-handling techniques Work with modern state-of-the-art large-scale machine learning techniques Learn to use Python code to implement a range of machine learning algorithms and techniques Who this book is for This Learning Path is for Python programmers who are looking to use machine learning algorithms to create real-world applications. It is ideal for Python professionals who want to work with large and complex datasets and Python developers and analysts or data scientists who are looking to add to their existing skills by accessing some of the most powerful recent trends in data science. Experience with Python, Jupyter Notebooks, and command-line execution together with a good level of mathematical knowledge to understand the concepts is expected. Machine learning basic knowledge is also expected.…

Condición: New.

Paperback. Condición: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

Digital. Condición: New. No detailed description available for "Python: Real World Machine Learning".

Kartoniert / Broschiert. Condición: New.

paperback. Condición: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

paperback. Condición: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

Kartoniert / Broschiert. Condición: New.

Kartoniert / Broschiert. Condición: New.