Jones aaron johnston benjamin (25 resultados)

Paperback. Condición: Good. No Jacket. Former library book; Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less.

Condición: Very Good. Former library copy. Pages intact with possible writing/highlighting. Binding strong with minor wear. Dust jackets/supplements may not be included. Includes library markings. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.

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Paperback. Condición: New. Design clever algorithms that can uncover interesting structures and hidden relationships in unstructured and unlabeled dataKey FeaturesLearn how to select the most suitable Python library to solve your problemCompare k-Nearest Neighbor (k-NN) and non-parametric methods and decide when to use themExplore the applications of neural networks using real-world datasetsBook DescriptionUnsupervised learning is a useful and practical solution in situations where labeled data is not available.Applied Unsupervised Learning with Python guides you in learning the best practices for using unsupervised learning techniques in tandem with Python libraries and extracting meaningful information from unstructured data. The book begins by explaining how basic clustering works to find similar data points in a set. Once you are well-versed with the k-means algorithm and how it operates, you'll learn what dimensionality reduction is and where to apply it. As you progress, you'll learn various neural network techniques and how they can improve your model. While studying the applications of unsupervised learning, you will also understand how to mine topics that are trending on Twitter and Facebook and build a news recommendation engine for users. Finally, you will be able to put your knowledge to work through interesting activities such as performing a Market Basket Analysis and identifying relationships between different products.By the end of this book, you will have the skills you need to confidently build your own models using Python.What you will learnUnderstand the basics and importance of clusteringBuild k-means, hierarchical, and DBSCAN clustering algorithms from scratch with built-in packagesExplore dimensionality reduction and its applicationsUse scikit-learn (sklearn) to implement and analyze principal component analysis (PCA) on the Iris datasetEmploy Keras to build autoencoder models for the CIFAR-10 datasetApply the Apriori algorithm with machine learning extensions (Mlxtend) to study transaction dataWho this book is forThis course is designed for developers, data scientists, and machine learning enthusiasts who are interested in unsupervised learning. Some familiarity with Python programming along with basic knowledge of mathematical concepts including exponents, square roots, means, and medians will be beneficial.…

Condición: New.

Condición: New. pp. 482.

Condición: New. pp. 550.

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Condición: New. In English.

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

Paperback. Condición: New. Design clever algorithms that can uncover interesting structures and hidden relationships in unstructured and unlabeled dataKey FeaturesLearn how to select the most suitable Python library to solve your problemCompare k-Nearest Neighbor (k-NN) and non-parametric methods and decide when to use themExplore the applications of neural networks using real-world datasetsBook DescriptionUnsupervised learning is a useful and practical solution in situations where labeled data is not available.Applied Unsupervised Learning with Python guides you in learning the best practices for using unsupervised learning techniques in tandem with Python libraries and extracting meaningful information from unstructured data. The book begins by explaining how basic clustering works to find similar data points in a set. Once you are well-versed with the k-means algorithm and how it operates, you'll learn what dimensionality reduction is and where to apply it. As you progress, you'll learn various neural network techniques and how they can improve your model. While studying the applications of unsupervised learning, you will also understand how to mine topics that are trending on Twitter and Facebook and build a news recommendation engine for users. Finally, you will be able to put your knowledge to work through interesting activities such as performing a Market Basket Analysis and identifying relationships between different products.By the end of this book, you will have the skills you need to confidently build your own models using Python.What you will learnUnderstand the basics and importance of clusteringBuild k-means, hierarchical, and DBSCAN clustering algorithms from scratch with built-in packagesExplore dimensionality reduction and its applicationsUse scikit-learn (sklearn) to implement and analyze principal component analysis (PCA) on the Iris datasetEmploy Keras to build autoencoder models for the CIFAR-10 datasetApply the Apriori algorithm with machine learning extensions (Mlxtend) to study transaction dataWho this book is forThis course is designed for developers, data scientists, and machine learning enthusiasts who are interested in unsupervised learning. Some familiarity with Python programming along with basic knowledge of mathematical concepts including exponents, square roots, means, and medians will be beneficial.…

Condición: New. Print on Demand pp. 482.

Condición: New. Print on Demand pp. 550.

Condición: New. PRINT ON DEMAND pp. 482.

Condición: New. PRINT ON DEMAND pp. 550.

Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. &Uumlber den AutorrnrnAaron Jones is a full-time senior data scientist and consultant. He has built models and data products while working in retail, media, and environmental science. Aaron is based in Seattle, Washington and has a particular i. …

Kartoniert / Broschiert. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Starting with the basics, Applied Unsupervised Learning with Python explains various techniques that you can apply to your data using the powerful Python libraries so that your unlabeled data reveals solutions to all your business questions.…