Da: BooksRun, Philadelphia, PA, U.S.A.
Prima edizione
Paperback. Condizione: Very Good. 1st ed. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.
EUR 23,91
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New.
Da: Lakeside Books, Benton Harbor, MI, U.S.A.
EUR 22,73
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New. Brand New! Not Overstocks or Low Quality Book Club Editions! Direct From the Publisher! We're not a giant, faceless warehouse organization! We're a small town bookstore that loves books and loves it's customers! Buy from Lakeside Books!
Paperback or Softback. Condizione: New. Time Series Algorithms Recipes: Implement Machine Learning and Deep Learning Techniques with Python. Book.
EUR 25,69
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: As New. Unread book in perfect condition.
Da: California Books, Miami, FL, U.S.A.
EUR 29,27
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New.
Condizione: New.
EUR 29,54
Quantità: 1 disponibili
Aggiungi al carrelloPaperback. Condizione: New. This book will teach you how to build recommender systems with machine learning algorithms using Python. Recommender systems have become an essential part of every internet-based business today.You'll start by learning basic concepts of recommender systems, with an overview of different types of recommender engines and how they function. Next, you will see how to build recommender systems with traditional algorithms such as market basket analysis and content- and knowledge-based recommender systems with NLP. The authors then demonstrate techniques such as collaborative filtering using matrix factorization and hybrid recommender systems that incorporate both content-based and collaborative filtering techniques. This is followed by a tutorial on building machine learning-based recommender systems using clustering and classification algorithms like K-means and random forest. The last chapters cover NLP, deep learning, and graph-based techniques to build a recommender engine. Each chapter includes data preparation, multiple ways to evaluate and optimize the recommender systems, supporting examples, and illustrations.By the end of this book, you will understand and be able to build recommender systems with various tools and techniques with machine learning, deep learning, and graph-based algorithms.What You Will LearnUnderstand and implement different recommender systems techniques with PythonEmploy popular methods like content- and knowledge-based, collaborative filtering, market basket analysis, and matrix factorization Build hybrid recommender systems that incorporate both content-based and collaborative filteringLeverage machine learning, NLP, and deep learning for building recommender systemsWho This Book Is ForData scientists, machine learning engineers, and Python programmers interested in building and implementing recommender systems to solve problems.
Da: GreatBookPrices, Columbia, MD, U.S.A.
EUR 28,10
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New.
Da: Lakeside Books, Benton Harbor, MI, U.S.A.
EUR 27,19
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New. Brand New! Not Overstocks or Low Quality Book Club Editions! Direct From the Publisher! We're not a giant, faceless warehouse organization! We're a small town bookstore that loves books and loves it's customers! Buy from Lakeside Books!
Paperback. Condizione: Good. No Jacket. Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less.
Condizione: As New. Unread book in perfect condition.
Da: California Books, Miami, FL, U.S.A.
EUR 33,71
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New.
Da: California Books, Miami, FL, U.S.A.
EUR 33,71
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New.
Da: GreatBookPrices, Columbia, MD, U.S.A.
EUR 31,57
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: As New. Unread book in perfect condition.
paperback. Condizione: Acceptable. The innre rhinges have come unglued. The copy shows minor external wear, but is in otherwise very good condition.
paperback. Condizione: Good. Some shelf wear.
Da: THE SAINT BOOKSTORE, Southport, Regno Unito
EUR 26,62
Quantità: 1 disponibili
Aggiungi al carrelloPaperback / softback. Condizione: New. New copy - Usually dispatched within 2 working days.
Da: GreatBookPrices, Columbia, MD, U.S.A.
EUR 40,33
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New.
Da: GreatBookPrices, Columbia, MD, U.S.A.
EUR 40,33
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New.
Da: Lakeside Books, Benton Harbor, MI, U.S.A.
EUR 39,14
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New. Brand New! Not Overstocks or Low Quality Book Club Editions! Direct From the Publisher! We're not a giant, faceless warehouse organization! We're a small town bookstore that loves books and loves it's customers! Buy from Lakeside Books!
EUR 42,79
Quantità: 1 disponibili
Aggiungi al carrelloPaperback. Condizione: New. 2nd ed. Focus on implementing end-to-end projects using Python and leverage state-of-the-art algorithms. This book teaches you to efficiently use a wide range of natural language processing (NLP) packages to: implement text classification, identify parts of speech, utilize topic modeling, text summarization, sentiment analysis, information retrieval, and many more applications of NLP. The book begins with text data collection, web scraping, and the different types of data sources. It explains how to clean and pre-process text data, and offers ways to analyze data with advanced algorithms. You then explore semantic and syntactic analysis of the text. Complex NLP solutions that involve text normalization are covered along with advanced pre-processing methods, POS tagging, parsing, text summarization, sentiment analysis, word2vec, seq2seq, and much more. The book presents the fundamentals necessary for applications of machine learning and deep learning in NLP. This second edition goes over advanced techniques to convert text to features such as Glove, Elmo, Bert, etc. It also includes an understanding of how transformers work, taking sentence BERT and GPT as examples. The final chapters explain advanced industrial applications of NLP with solution implementation and leveraging the power of deep learning techniques for NLP problems. It also employs state-of-the-art advanced RNNs, such as long short-term memory, to solve complex text generation tasks. After reading this book, you will have a clear understanding of the challenges faced by different industries and you will have worked on multiple examples of implementing NLP in the real world.What You Will LearnKnow the core concepts of implementing NLP and various approaches to natural language processing (NLP), including NLP using Python libraries such as NLTK, textblob, SpaCy, Standford CoreNLP, and moreImplement text pre-processing and feature engineering in NLP, including advanced methods of feature engineeringUnderstand and implement the concepts of information retrieval, text summarization, sentiment analysis, text classification, and other advanced NLP techniques leveraging machine learning and deep learningWho This Book Is ForData scientists who want to refresh and learn various concepts of natural language processing (NLP) through coding exercises.
Condizione: New.
Da: BargainBookStores, Grand Rapids, MI, U.S.A.
Paperback or Softback. Condizione: New. Computer Vision Projects with Pytorch: Design and Develop Production-Grade Models. Book.
Paperback or Softback. Condizione: New. Natural Language Processing Projects: Build Next-Generation NLP Applications Using AI Techniques. Book.
Paperback or Softback. Condizione: New. Natural Language Processing Recipes: Unlocking Text Data with Machine Learning and Deep Learning Using Python. Book.
Paperback or Softback. Condizione: New. Applied Recommender Systems with Python: Build Recommender Systems with Deep Learning, Nlp and Graph-Based Techniques. Book.
Da: Grand Eagle Retail, Bensenville, IL, U.S.A.
Prima edizione
Paperback. Condizione: new. Paperback. This book will teach you how to build recommender systems with machine learning algorithms using Python. Recommender systems have become an essential part of every internet-based business today.You'll start by learning basic concepts of recommender systems, with an overview of different types of recommender engines and how they function. Next, you will see how to build recommender systems with traditional algorithms such as market basket analysis and content- and knowledge-based recommender systems with NLP. The authors then demonstrate techniques such as collaborative filtering using matrix factorization and hybrid recommender systems that incorporate both content-based and collaborative filtering techniques. This is followed by a tutorial on building machine learning-based recommender systems using clustering and classification algorithms like K-means and random forest. The last chapters cover NLP, deep learning, and graph-based techniques to build a recommender engine. Each chapter includes data preparation, multiple ways to evaluate and optimize the recommender systems, supporting examples, and illustrations.By the end of this book, you will understand and be able to build recommender systems with various tools and techniques with machine learning, deep learning, and graph-based algorithms.What You Will LearnUnderstand and implement different recommender systems techniques with PythonEmploy popular methods like content- and knowledge-based, collaborative filtering, market basket analysis, and matrix factorization Build hybrid recommender systems that incorporate both content-based and collaborative filteringLeverage machine learning, NLP, and deep learning for building recommender systemsWho This Book Is ForData scientists, machine learning engineers, and Python programmers interested in building and implementing recommender systems to solve problems. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Da: GreatBookPrices, Columbia, MD, U.S.A.
EUR 43,94
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: As New. Unread book in perfect condition.
Condizione: As New. Unread book in perfect condition.