Ayyadevara, V Kishore Pro machine learning algorithms 9781484235638

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Автор: Ayyadevara, V Kishore
Название: Pro machine learning algorithms
ISBN: 9781484235638
Издательство: Springer
Классификация:

Компьютерное программирование / разработка по

Парадигмы программирования / Обучение программированию

Алгоритмы и структуры данных

Языки программирования и описания сценариев: общие сведения

Базы данных

Искусственный интеллект

Обработка изображений

ISBN-10: 1484235630
Обложка/Формат: Paperback
Страницы: 372
Вес: 0.77 кг.
Дата издания: 01.07.2018
Язык: English
Издание: 1st ed.
Иллюстрации: 306 illustrations, color; 155 illustrations, black and white; v, 319 p. 461 illus., 306 illus. in color.
Размер: 254 x 179 x 23
Читательская аудитория: General (us: trade)
Подзаголовок: A hands-on approach to implementing algorithms in python and r
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание:

Bridge the gap between a high-level understanding of how an algorithm works and knowing the nuts and bolts to tune your models better. This book will give you the confidence and skills when developing all the major machine learning models. In Pro Machine Learning Algorithms, you will first develop the algorithm in Excel so that you get a practical understanding of all the levers that can be tuned in a model, before implementing the models in Python/R.

You will cover all the major algorithms: supervised and unsupervised learning, which include linear/logistic regression; k-means clustering; PCA; recommender system; decision tree; random forest; GBM; and neural networks. You will also be exposed to the latest in deep learning through CNNs, RNNs, and word2vec for text mining. You will be learning not only the algorithms, but also the concepts of feature engineering to maximize the performance of a model. You will see the theory along with case studies, such as sentiment classification, fraud detection, recommender systems, and image recognition, so that you get the best of both theory and practice for the vast majority of the machine learning algorithms used in industry. Along with learning the algorithms, you will also be exposed to running machine-learning models on all the major cloud service providers.

You are expected to have minimal knowledge of statistics/software programming and by the end of this book you should be able to work on a machine learning project with confidence.

What You Will Learn

Get an in-depth understanding of all the major machine learning and deep learning algorithms Fully appreciate the pitfalls to avoid while building modelsImplement machine learning algorithms in the cloud Follow a hands-on approach through case studies for each algorithmGain the tricks of ensemble learning to build more accurate modelsDiscover the basics of programming in R/Python and the Keras framework for deep learning

Who This Book Is For

Business analysts/ IT professionals who want to transition into data science roles. Data scientists who want to solidify their knowledge in machine learning.

Дополнительное описание:

Chapter 1: Basics of Machine Learning.- Chapter 2: Linear regression .- Chapter 3: Logistic regression.- Chapter 4: Decision tree.- Chapter 5: Random forest.- Chapter 6: GBM.- Chapter 7: Neural network.- Chapter 8: word2vec.- Chapter 9:

Pro machine learning algorithms, Ayyadevara, V Kishore