Kulkarni anoosh (71 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 23,93
EUR 2,28 spedizioneSpedito in U.S.A.Quantità: Più di 20 disponibili
Condizione: New.
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 25,71
EUR 2,28 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 29,29
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 27,10
EUR 2,28 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 29,46
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.
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 31,32
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 32,49
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 30,85
EUR 2,28 spedizioneSpedito in U.S.A.Quantità: 4 disponibili
Condizione: As New. Unread book in perfect condition.
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 33,73
Spedizione gratuitaSpedito in U.S.A.Quantità: Più di 20 disponibili
Condizione: New.
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 34,02
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.
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 38,14
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.
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 37,46
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 37,46
EUR 4,30 spedizioneSpedito in U.S.A.Quantità: 1 disponibili
paperback. Condizione: Good. Some shelf wear.
- Brossura
Da: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 41,32
EUR 2,28 spedizioneSpedito in U.S.A.Quantità: 15 disponibili
Condizione: New.
- Brossura
Da: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
Contatta il venditoreVenditore con 5 stelleCondizione: Usato - Come nuovo
EUR 44,37
EUR 2,28 spedizioneSpedito in U.S.A.Quantità: 15 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
- Prima edizione
Da: Kennys Bookshop and Art Galleries Ltd., Galway, GY, IrlandaKennys Bookshop and Art Galleries Ltd.
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 35,26
EUR 10,50 spedizioneSpedito da Irlanda a U.S.A.Quantità: 15 disponibili
Condizione: New. 2022. 1st ed. paperback. . . . . .
- Brossura
Da: California Books, Miami, FL, U.S.A.California Books
Contatta il venditoreVenditore con 4 stelleCondizione: Nuovo
EUR 47,93
Spedizione gratuitaSpedito in U.S.A.Quantità: Più di 20 disponibili
Condizione: New.
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: Revaluation Books, Exeter, , Regno UnitoRevaluation Books
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 37,30
EUR 11,59 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 2 disponibili
Paperback. Condizione: Brand New. 190 pages. 9.25x6.10x0.43 inches. In Stock.
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: Ria Christie Collections, Uxbridge, Regno UnitoRia Christie Collections
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 35,59
EUR 13,89 spedizioneSpedito da Regno Unito a U.S.A.Quantità: Più di 20 disponibili
Condizione: New. In.
Time Series Algorithms Recipes 1st ed.
Kulkarni, Akshay R;shivananda, Adarsha;kulkarni, Anoosh;krishnan, V Adithya
- Brossura
Da: GreatBookPricesUK, Woodford Green, Regno UnitoGreatBookPricesUK
Contatta il venditoreVenditore con 5 stelleCondizione: Usato - Come nuovo
EUR 31,96
EUR 17,39 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 1 disponibili
Condizione: As New. Unread book in perfect condition.
Time Series Algorithms Recipes 1st ed.
Kulkarni, Akshay R;shivananda, Adarsha;kulkarni, Anoosh;krishnan, V Adithya
- Brossura
Da: GreatBookPricesUK, Woodford Green, Regno UnitoGreatBookPricesUK
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 33,15
EUR 17,39 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 1 disponibili
Condizione: New.
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: Kennys Bookstore, Olney, MD, U.S.A.Kennys Bookstore
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 42,97
EUR 9,05 spedizioneSpedito in U.S.A.Quantità: 15 disponibili
Condizione: New. 2022. 1st ed. paperback. . . . . . Books ship from the US and Ireland.
Applied Generative Ai for Beginners : Practical Knowledge on Diffusion Models, Chatgpt, and Other Llms
Kulkarni, Akshay; Shivananda, Adarsha; Kulkarni, Anoosh; Gudivada, Dilip
- Brossura
Da: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 50,49
EUR 2,28 spedizioneSpedito in U.S.A.Quantità: Più di 20 disponibili
Condizione: New.
- Brossura
- Prima edizione
Da: Rarewaves USA, OSWEGO, IL, U.S.A.Rarewaves USA
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 53,85
Spedizione gratuitaSpedito in U.S.A.Quantità: 8 disponibili
Paperback. Condizione: New. 1st ed. Leverage machine learning and deep learning techniques to build fully-fledged natural language processing (NLP) projects. Projects throughout this book grow in complexity and showcase methodologies, optimizing tips, and tricks to solve various business problems. You will use modern Python libr…aries and algorithms to build end-to-end NLP projects. The book starts with an overview of natural language processing (NLP) and artificial intelligence to provide a quick refresher on algorithms. Next, it covers end-to-end NLP projects beginning with traditional algorithms and projects such as customer review sentiment and emotion detection, topic modeling, and document clustering. From there, it delves into e-commerce related projects such as product categorization using the description of the product, a search engine to retrieve the relevant content, and a content-based recommendation system to enhance user experience. Moving forward, it explains how to build systems to find similar sentences using contextual embedding, summarizing huge documents using recurrent neural networks (RNN), automatic word suggestion using long short-term memory networks (LSTM), and how to build a chatbot using transfer learning. It concludes with an exploration of next-generation AI and algorithms in the research space. By the end of this book, you will have the knowledge needed to solve various business problems using NLP techniques.What You Will LearnImplement full-fledged intelligent NLP applications with PythonTranslate real-world business problem on text data with NLP techniquesLeverage machine learning and deep learning techniques to perform smart language processingGain hands-on experience implementing end-to-end search engine information retrieval, text summarization, chatbots, text generation, document clustering and product classification,and moreWho This Book Is ForData scientists, machine learning engineers, and deep learning professionals looking to build natural language applications using Python.
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: GreatBookPricesUK, Woodford Green, Regno UnitoGreatBookPricesUK
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 36,87
EUR 17,39 spedizioneSpedito da Regno Unito a 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: GreatBookPricesUK, Woodford Green, Regno UnitoGreatBookPricesUK
Contatta il venditoreVenditore con 5 stelleCondizione: Usato - Come nuovo
EUR 37,78
EUR 17,39 spedizioneSpedito da Regno Unito a U.S.A.Quantità: Più di 20 disponibili
Condizione: As New. Unread book in perfect 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: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
Contatta il venditoreVenditore con 5 stelleCondizione: Usato - Come nuovo
EUR 54,38
EUR 2,28 spedizioneSpedito in U.S.A.Quantità: Più di 20 disponibili
Condizione: As New. Unread book in perfect condition.
Applied Recommender Systems with Python: Build Recommender Systems with Deep Learning, NLP and Graph-Based Techniques
Kulkarni, Akshay Akshay Kulkarni, Adarsha Shivananda, Anoosh Kulkarni, V Adithya Krishnan,
- Brossura
Da: Chiron Media, Wallingford, , Regno UnitoChiron Media
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 39,09
EUR 17,96 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 1 disponibili
paperback. 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: Ria Christie Collections, Uxbridge, Regno UnitoRia Christie Collections
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 45,98
EUR 13,89 spedizioneSpedito da Regno Unito a U.S.A.Quantità: Più di 20 disponibili
Condizione: New. In.
- Brossura
- Prima edizione
Da: Rarewaves.com USA, London, LONDO, Regno UnitoRarewaves.com USA
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 60,05
Spedizione gratuitaSpedito da Regno Unito a U.S.A.Quantità: 8 disponibili
Paperback. Condizione: New. 1st ed. Leverage machine learning and deep learning techniques to build fully-fledged natural language processing (NLP) projects. Projects throughout this book grow in complexity and showcase methodologies, optimizing tips, and tricks to solve various business problems. You will use modern Python libr…aries and algorithms to build end-to-end NLP projects. The book starts with an overview of natural language processing (NLP) and artificial intelligence to provide a quick refresher on algorithms. Next, it covers end-to-end NLP projects beginning with traditional algorithms and projects such as customer review sentiment and emotion detection, topic modeling, and document clustering. From there, it delves into e-commerce related projects such as product categorization using the description of the product, a search engine to retrieve the relevant content, and a content-based recommendation system to enhance user experience. Moving forward, it explains how to build systems to find similar sentences using contextual embedding, summarizing huge documents using recurrent neural networks (RNN), automatic word suggestion using long short-term memory networks (LSTM), and how to build a chatbot using transfer learning. It concludes with an exploration of next-generation AI and algorithms in the research space. By the end of this book, you will have the knowledge needed to solve various business problems using NLP techniques.What You Will LearnImplement full-fledged intelligent NLP applications with PythonTranslate real-world business problem on text data with NLP techniquesLeverage machine learning and deep learning techniques to perform smart language processingGain hands-on experience implementing end-to-end search engine information retrieval, text summarization, chatbots, text generation, document clustering and product classification,and moreWho This Book Is ForData scientists, machine learning engineers, and deep learning professionals looking to build natural language applications using Python.
