Kulkarni akshay (193 risultati)
Time Series Algorithms Recipes 1st ed.
Kulkarni, Akshay R;shivananda, Adarsha;kulkarni, Anoosh;krishnan, V Adithya
- Brossura
Da: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 23,92
EUR 2,27 spedizioneSpedito in U.S.A.Quantità: Più di 20 disponibili
Condizione: New.
- Brossura
Da: Lakeside Books, Benton Harbor, MI, U.S.A.Lakeside Books
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 22,73
EUR 3,44 spedizioneSpedito in U.S.A.Quantità: Più di 20 disponibili
Condizione: 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.
- Brossura
Da: BargainBookStores, Grand Rapids, MI, U.S.A.BargainBookStores
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 26,91
Spedizione gratuitaSpedito in U.S.A.Quantità: 5 disponibili
Paperback or Softback. Condizione: New. Time Series Algorithms Recipes: Implement Machine Learning and Deep Learning Techniques with Python. Book.
Time Series Algorithms Recipes 1st ed.
Kulkarni, Akshay R;shivananda, Adarsha;kulkarni, Anoosh;krishnan, V Adithya
- Brossura
Da: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
Contatta il venditoreVenditore con 5 stelleCondizione: Usato - Come nuovo
EUR 25,69
EUR 2,27 spedizioneSpedito in U.S.A.Quantità: Più di 20 disponibili
Condizione: As New. Unread book in perfect condition.
Time Series Algorithms Recipes: Implement Machine Learning and Deep Learning Techniques with Python
Kulkarni, Akshay R; Shivananda, Adarsha; Kulkarni, Anoosh; Krishnan, V Adithya
- Brossura
Da: California Books, Miami, FL, U.S.A.California Books
Contatta il venditoreVenditore con 4 stelleCondizione: Nuovo
EUR 29,28
Spedizione gratuitaSpedito in U.S.A.Quantità: Più di 20 disponibili
Condizione: New.
Applied Recommender Systems with Python : Build Recommender Systems with Deep Learning, NLP and Graph-Based Techniques
Kulkarni, Akshay; Shivananda, Adarsha; Kulkarni, Anoosh; Krishnan, V Adithya
- Brossura
Da: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 27,09
EUR 2,27 spedizioneSpedito in U.S.A.Quantità: 4 disponibili
Condizione: New.
Applied Recommender Systems with Python
V Adithya Krishnan, Akshay Kulkarni, Anoosh Kulkarni, Adarsha Shivananda
- Brossura
Da: Rarewaves.com USA, London, LONDO, Regno UnitoRarewaves.com USA
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 29,44
Spedizione gratuitaSpedito da Regno Unito a U.S.A.Quantità: 1 disponibili
Paperback. 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 recom…mender 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.
- Brossura
Da: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 28,11
EUR 2,27 spedizioneSpedito in U.S.A.Quantità: Più di 20 disponibili
Condizione: New.
- Brossura
Da: Lakeside Books, Benton Harbor, MI, U.S.A.Lakeside Books
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 27,19
EUR 3,44 spedizioneSpedito in U.S.A.Quantità: Più di 20 disponibili
Condizione: 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.
Time Series Algorithms Recipes
V Adithya Krishnan, Akshay R Kulkarni, Adarsha Shivananda, Anoosh Kulkarni
- Brossura
- Prima edizione
Da: Rarewaves USA, OSWEGO, IL, U.S.A.Rarewaves USA
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 31,30
Spedizione gratuitaSpedito in U.S.A.Quantità: 8 disponibili
Paperback. Condizione: New. 1st ed. This book teaches the practical implementation of various concepts for time series analysis and modeling with Python through problem-solution-style recipes, starting with data reading and preprocessing. It begins with the fundamentals of time series forecasting using statistical modeling metho…ds like AR (autoregressive), MA (moving-average), ARMA (autoregressive moving-average), and ARIMA (autoregressive integrated moving-average). Next, you'll learn univariate and multivariate modeling using different open-sourced packages like Fbprohet, stats model, and sklearn. You'll also gain insight into classic machine learning-based regression models like randomForest, Xgboost, and LightGBM for forecasting problems. The book concludes by demonstrating the implementation of deep learning models (LSTMs and ANN) for time series forecasting. Each chapter includes several code examples and illustrations. After finishing this book,you will have a foundational understanding of various concepts relating to time series and its implementation in Python. What You Will LearnImplement various techniques in time series analysis using Python.Utilize statistical modeling methods such as AR (autoregressive), MA (moving-average), ARMA (autoregressive moving-average) and ARIMA (autoregressive integrated moving-average) for time series forecasting Understand univariate and multivariate modeling for time series forecastingForecast using machine learning and deep learning techniques such as GBM and LSTM (long short-term memory) Who This Book Is ForData Scientists, Machine Learning Engineers, and software developers interested in time series analysis.
- Brossura
Da: ThriftBooks-Dallas, Dallas, TX, U.S.A.ThriftBooks-Dallas
Contatta il venditoreVenditore con 5 stelleCondizione: Usato - Buono
EUR 32,47
Spedizione gratuitaSpedito in U.S.A.Quantità: 1 disponibili
Paperback. Condizione: Good. No Jacket. Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less.
Applied Recommender Systems with Python : Build Recommender Systems with Deep Learning, NLP and Graph-Based Techniques
Kulkarni, Akshay; Shivananda, Adarsha; Kulkarni, Anoosh; Krishnan, V Adithya
- Brossura
Da: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
Contatta il venditoreVenditore con 5 stelleCondizione: Usato - Come nuovo
EUR 30,84
EUR 2,27 spedizioneSpedito in U.S.A.Quantità: 4 disponibili
Condizione: As New. Unread book in perfect condition.
- Brossura
Da: California Books, Miami, FL, U.S.A.California Books
Contatta il venditoreVenditore con 4 stelleCondizione: Nuovo
EUR 33,71
Spedizione gratuitaSpedito in U.S.A.Quantità: Più di 20 disponibili
Condizione: New.
Applied Recommender Systems with Python: Build Recommender Systems with Deep Learning, NLP and Graph-Based Techniques
Kulkarni, Akshay; Shivananda, Adarsha; Kulkarni, Anoosh; Krishnan, V Adithya
- Brossura
Da: California Books, Miami, FL, U.S.A.California Books
Contatta il venditoreVenditore con 4 stelleCondizione: Nuovo
EUR 33,71
Spedizione gratuitaSpedito in U.S.A.Quantità: Più di 20 disponibili
Condizione: New.
- Brossura
Da: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
Contatta il venditoreVenditore con 5 stelleCondizione: Usato - Come nuovo
EUR 31,58
EUR 2,27 spedizioneSpedito in U.S.A.Quantità: Più di 20 disponibili
Condizione: As New. Unread book in perfect condition.
Time Series Algorithms Recipes
V Adithya Krishnan, Akshay R Kulkarni, Adarsha Shivananda, Anoosh Kulkarni
- Brossura
- Prima edizione
Da: Rarewaves.com USA, London, LONDO, Regno UnitoRarewaves.com USA
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 34,01
Spedizione gratuitaSpedito da Regno Unito a U.S.A.Quantità: 8 disponibili
Paperback. Condizione: New. 1st ed. This book teaches the practical implementation of various concepts for time series analysis and modeling with Python through problem-solution-style recipes, starting with data reading and preprocessing. It begins with the fundamentals of time series forecasting using statistical modeling metho…ds like AR (autoregressive), MA (moving-average), ARMA (autoregressive moving-average), and ARIMA (autoregressive integrated moving-average). Next, you'll learn univariate and multivariate modeling using different open-sourced packages like Fbprohet, stats model, and sklearn. You'll also gain insight into classic machine learning-based regression models like randomForest, Xgboost, and LightGBM for forecasting problems. The book concludes by demonstrating the implementation of deep learning models (LSTMs and ANN) for time series forecasting. Each chapter includes several code examples and illustrations. After finishing this book,you will have a foundational understanding of various concepts relating to time series and its implementation in Python. What You Will LearnImplement various techniques in time series analysis using Python.Utilize statistical modeling methods such as AR (autoregressive), MA (moving-average), ARMA (autoregressive moving-average) and ARIMA (autoregressive integrated moving-average) for time series forecasting Understand univariate and multivariate modeling for time series forecastingForecast using machine learning and deep learning techniques such as GBM and LSTM (long short-term memory) Who This Book Is ForData Scientists, Machine Learning Engineers, and software developers interested in time series analysis.
- Brossura
Da: Rarewaves USA, OSWEGO, IL, U.S.A.Rarewaves USA
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 36,64
Spedizione gratuitaSpedito in U.S.A.Quantità: 8 disponibili
Paperback. Condizione: New. Gain a working knowledge of prescriptive AI, its history, and its current and future trends. This book will help you evaluate different AI-driven predictive analytics techniques and help you incorporate decision intelligence into your business workflow through real-world examples.The book kicks off wi…th an introduction to decision intelligence and provides insight into prescriptive AI and how it can be woven into various business strategies and frameworks. You'll then be introduced to different decision intelligence methodologies and how to implement them, along with advantages and limitations of each. Digging deeper, the authors then walk you through how to perform simulations and interpret the results. A full chapter is devoted to embedding decision intelligence processes and outcomes into your business workflow using various applications. The book concludes by exploring different cognitive biases humans are prone to, and how those biasescan be eliminated by combining machine and human intelligence.Upon completing this book, you will understand prescriptive AI, tools, and techniques and will be ready to incorporate them into your business workflow.What You Will LearnImplement full-fledged decision intelligence applications using PythonLeverage the tools, techniques, and methodologies for prescriptive AIUnderstand how prescriptive AI can be used in different domains through practical examplesInterpret results and integrate them into your decision makingWho This Book Is ForData Scientists and Machine Learning Engineers, as well as business professionals who want to understand how AI-driven decision intelligence can help grow their business.
Applied Recommender Systems with Python
V Adithya Krishnan, Akshay Kulkarni, Anoosh Kulkarni, Adarsha Shivananda
- Brossura
Da: Rarewaves USA, OSWEGO, IL, U.S.A.Rarewaves USA
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 38,11
Spedizione gratuitaSpedito in U.S.A.Quantità: 8 disponibili
Paperback. 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 recom…mender 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.
- Brossura
Da: Rarewaves.com USA, London, LONDO, Regno UnitoRarewaves.com USA
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 39,71
Spedizione gratuitaSpedito da Regno Unito a U.S.A.Quantità: 8 disponibili
Paperback. Condizione: New. Gain a working knowledge of prescriptive AI, its history, and its current and future trends. This book will help you evaluate different AI-driven predictive analytics techniques and help you incorporate decision intelligence into your business workflow through real-world examples.The book kicks off wi…th an introduction to decision intelligence and provides insight into prescriptive AI and how it can be woven into various business strategies and frameworks. You'll then be introduced to different decision intelligence methodologies and how to implement them, along with advantages and limitations of each. Digging deeper, the authors then walk you through how to perform simulations and interpret the results. A full chapter is devoted to embedding decision intelligence processes and outcomes into your business workflow using various applications. The book concludes by exploring different cognitive biases humans are prone to, and how those biasescan be eliminated by combining machine and human intelligence.Upon completing this book, you will understand prescriptive AI, tools, and techniques and will be ready to incorporate them into your business workflow.What You Will LearnImplement full-fledged decision intelligence applications using PythonLeverage the tools, techniques, and methodologies for prescriptive AIUnderstand how prescriptive AI can be used in different domains through practical examplesInterpret results and integrate them into your decision makingWho This Book Is ForData Scientists and Machine Learning Engineers, as well as business professionals who want to understand how AI-driven decision intelligence can help grow their business.
Applied Generative AI for Beginners: Practical Knowledge on Diffusion Models, ChatGPT, and Other LLMs
Kulkarni, Akshay,Shivananda, Adarsha,Kulkarni, Anoosh,Gudivada, Dilip
- Brossura
Da: Books From California, Simi Valley, CA, U.S.A.Books From California
Contatta il venditoreVenditore con 4 stelleCondizione: Usato - Discreto
EUR 37,44
EUR 4,30 spedizioneSpedito in U.S.A.Quantità: 1 disponibili
paperback. Condizione: Acceptable. The innre rhinges have come unglued. The copy shows minor external wear, but is in otherwise very good condition.
Applied Generative AI for Beginners: Practical Knowledge on Diffusion Models, ChatGPT, and Other LLMs
Kulkarni, Akshay,Shivananda, Adarsha,Kulkarni, Anoosh,Gudivada, Dilip
- Brossura
Da: Books From California, Simi Valley, CA, U.S.A.Books From California
Contatta il venditoreVenditore con 4 stelleCondizione: Usato - Buono
EUR 37,44
EUR 4,30 spedizioneSpedito in U.S.A.Quantità: 1 disponibili
paperback. Condizione: Good. Some shelf wear.
- Brossura
Da: THE SAINT BOOKSTORE, Southport, , Regno UnitoTHE SAINT BOOKSTORE
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 26,63
EUR 14,85 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 1 disponibili
Paperback / softback. Condizione: New. New copy - Usually dispatched within 2 working days.
- Brossura
Da: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 40,34
EUR 2,27 spedizioneSpedito in U.S.A.Quantità: Più di 20 disponibili
Condizione: New.
- Brossura
Da: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 40,34
EUR 2,27 spedizioneSpedito in U.S.A.Quantità: Più di 20 disponibili
Condizione: New.
- Brossura
Da: Lakeside Books, Benton Harbor, MI, U.S.A.Lakeside Books
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 39,15
EUR 3,44 spedizioneSpedito in U.S.A.Quantità: Più di 20 disponibili
Condizione: 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.
- Brossura
Da: Rarewaves.com USA, London, LONDO, Regno UnitoRarewaves.com USA
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 42,80
Spedizione gratuitaSpedito da Regno Unito a U.S.A.Quantità: 1 disponibili
Paperback. 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 summari…zation, 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.
- Brossura
Da: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 41,30
EUR 2,27 spedizioneSpedito in U.S.A.Quantità: 15 disponibili
Condizione: New.
- Brossura
Da: BargainBookStores, Grand Rapids, MI, U.S.A.BargainBookStores
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 43,65
Spedizione gratuitaSpedito in U.S.A.Quantità: 5 disponibili
Paperback or Softback. Condizione: New. Computer Vision Projects with Pytorch: Design and Develop Production-Grade Models. Book.
- Brossura
Da: BargainBookStores, Grand Rapids, MI, U.S.A.BargainBookStores
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 43,65
Spedizione gratuitaSpedito in U.S.A.Quantità: 5 disponibili
Paperback or Softback. Condizione: New. Natural Language Processing Projects: Build Next-Generation NLP Applications Using AI Techniques. Book.
- Brossura
Da: BargainBookStores, Grand Rapids, MI, U.S.A.BargainBookStores
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 43,65
Spedizione gratuitaSpedito in U.S.A.Quantità: 5 disponibili
Paperback or Softback. Condizione: New. Natural Language Processing Recipes: Unlocking Text Data with Machine Learning and Deep Learning Using Python. Book.
