Machine Learning with PySpark. With Natural Language Processing and Recommender Systems. 2nd Ed. 244699
Код товару: 244699Паперова книга
-
ISBN9781484277768
-
Бренд
-
Автор
-
Рік2022
-
МоваАнглійська
-
ІлюстраціїЧорно-білі
-
ЖанрАналіз даних, Бази даних
Master the new features in PySpark 3.1 to develop data-driven, intelligent applications. This updated edition covers topics ranging from building scalable machine learning models, to natural language processing, to recommender systems.
Machine Learning with PySpark, Second Edition begins with the fundamentals of Apache Spark, including the latest updates to the framework. Next, you will learn the full spectrum of traditional machine learning algorithm implementations, along with natural language processing and recommender systems. You’ll gain familiarity with the critical process of selecting machine learning algorithms, data ingestion, and data processing to solve business problems. You’ll see a demonstration of how to build supervised machine learning models such as linear regression, logistic regression, decision trees, and random forests. You’ll also learn how to automate the steps using Spark pipelines, followed by unsupervised models such as K-means and hierarchical clustering. A section on Natural Language Processing (NLP) covers text processing, text mining, and embeddings for classification. This new edition also introduces Koalas in Spark and how to automate data workflow using Airflow and PySpark’s latest ML library.
After completing this book, you will understand how to use PySpark’s machine learning library to build and train various machine learning models, along with related components such as data ingestion, processing and visualization to develop data-driven intelligent applications
Machine Learning with PySpark, Second Edition begins with the fundamentals of Apache Spark, including the latest updates to the framework. Next, you will learn the full spectrum of traditional machine learning algorithm implementations, along with natural language processing and recommender systems. You’ll gain familiarity with the critical process of selecting machine learning algorithms, data ingestion, and data processing to solve business problems. You’ll see a demonstration of how to build supervised machine learning models such as linear regression, logistic regression, decision trees, and random forests. You’ll also learn how to automate the steps using Spark pipelines, followed by unsupervised models such as K-means and hierarchical clustering. A section on Natural Language Processing (NLP) covers text processing, text mining, and embeddings for classification. This new edition also introduces Koalas in Spark and how to automate data workflow using Airflow and PySpark’s latest ML library.
After completing this book, you will understand how to use PySpark’s machine learning library to build and train various machine learning models, along with related components such as data ingestion, processing and visualization to develop data-driven intelligent applications
- You will:
- Build a spectrum of supervised and unsupervised machine learning algorithms
- Use PySpark's machine learning library to implement machine learning and recommender systems
- Leverage the new features in PySpark’s machine learning library
- Understand data processing using Koalas in Spark
- Handle issues around feature engineering, class balance, bias and variance, and cross validation to build optimally fit models
1'600 ₴
Купити
Monobank
от 180 ₴ / міс.
до 10 платежей
Покупка частинами Monobank
₴ / місяць
Для використання функції «Покупка частинами» необхідно мати картку Monobank.
Розділивши оплату на певну кількість платежів (від 3 до 10),
ви платите лише одну частину. Решта – раз на місяць списуватиметься з вашої карти.
Послуга може бути використана при замовлення на суму від 600 грн.
Увага! При покупці частинами знижки на товари не враховуються.
Щоб скористатися цією функцією, додайте в кошик товарів на суму від 600 грн.
На сторінці оформлення замовлення вкажіть спосіб оплати «Покупка частинами Monobank». Підтвердьте покупку у програмі Monobank.
-
Нова ПоштаБезкоштовно від
3'000,00 ₴ -
УкрпоштаБезкоштовно від
1'000,00 ₴ -
Meest ПоштаБезкоштовно від
3'000,00 ₴
Інші книги Apress
Характеристики
- Бренд
- Вага, г460
- Автор
- КатегоріяКомп'ютерна література
- Номер видання2-ге вид.
- Рік2022
- Сторінок220
- Формат180х255 мм
- ОбкладинкаМ'яка
- Тип паперуОфсетний
- МоваАнглійська
- ІлюстраціїЧорно-білі
- ЖанрАналіз данихБази даних
- Вік16+
Від видавця
Master the new features in PySpark 3.1 to develop data-driven, intelligent applications. This updated edition covers topics ranging from building scalable machine learning models, to natural language processing, to recommender systems.
Machine Learning with PySpark, Second Edition begins with the fundamentals of Apache Spark, including the latest updates to the framework. Next, you will learn the full spectrum of traditional machine learning algorithm implementations, along with natural language processing and recommender systems. You’ll gain familiarity with the critical process of selecting machine learning algorithms, data ingestion, and data processing to solve business problems. You’ll see a demonstration of how to build supervised machine learning models such as linear regression, logistic regression, decision trees, and random forests. You’ll also learn how to automate the steps using Spark pipelines, followed by unsupervised models such as K-means and hierarchical clustering. A section on Natural Language Processing (NLP) covers text processing, text mining, and embeddings for classification. This new edition also introduces Koalas in Spark and how to automate data workflow using Airflow and PySpark’s latest ML library.
After completing this book, you will understand how to use PySpark’s machine learning library to build and train various machine learning models, along with related components such as data ingestion, processing and visualization to develop data-driven intelligent applications
Machine Learning with PySpark, Second Edition begins with the fundamentals of Apache Spark, including the latest updates to the framework. Next, you will learn the full spectrum of traditional machine learning algorithm implementations, along with natural language processing and recommender systems. You’ll gain familiarity with the critical process of selecting machine learning algorithms, data ingestion, and data processing to solve business problems. You’ll see a demonstration of how to build supervised machine learning models such as linear regression, logistic regression, decision trees, and random forests. You’ll also learn how to automate the steps using Spark pipelines, followed by unsupervised models such as K-means and hierarchical clustering. A section on Natural Language Processing (NLP) covers text processing, text mining, and embeddings for classification. This new edition also introduces Koalas in Spark and how to automate data workflow using Airflow and PySpark’s latest ML library.
After completing this book, you will understand how to use PySpark’s machine learning library to build and train various machine learning models, along with related components such as data ingestion, processing and visualization to develop data-driven intelligent applications
- You will:
- Build a spectrum of supervised and unsupervised machine learning algorithms
- Use PySpark's machine learning library to implement machine learning and recommender systems
- Leverage the new features in PySpark’s machine learning library
- Understand data processing using Koalas in Spark
- Handle issues around feature engineering, class balance, bias and variance, and cross validation to build optimally fit models
Machine Learning with PySpark. With Natural Language Processing and Recommender Systems. 2nd Ed.
1'600 ₴
Вас може зацікавити
244793
2'400 ₴
244698
1'900 ₴
244699
1'600 ₴
244707
1'600 ₴
Персонально для вас
Відгуки про Machine Learning with PySpark. With Natural Language Processing and Recommender Systems. 2nd Ed.