Shivananda v (33 Ergebnisse)

Soft cover. Zustand: Very Good. 96 pp., illustrations, map.

Paperback. Zustand: 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.…

Zustand: New.

Paperback. Zustand: New. 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 methods 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.…

Paperback. Zustand: 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.…

Zustand: New.

Zustand: New. pp. xvi + 276.

Zustand: New. pp. xiv + 126.

Zustand: New. pp. xvi + 276.

Zustand: New. pp. xiv + 126.

paperback. Zustand: New. Brand new book, sourced directly from publisher. Dispatch time is 3-4 days from our warehouse. Book will be sent in robust, secure packaging to ensure it reaches you securely.

Zustand: New. 2022. 1st ed. paperback. . . . . .

Paperback. Zustand: Brand New. 190 pages. 9.25x6.10x0.43 inches. In Stock.

Zustand: As New. Unread book in perfect condition.

Zustand: New. 2022. 1st ed. paperback. . . . . . Books ship from the US and Ireland.

Zustand: New.

Zustand: New.

Zustand: As New. Unread book in perfect condition.

Paperback. Zustand: Brand New. 261 pages. 10.00x7.01x0.55 inches. In Stock.

Hardcover. Zustand: New. 1st Edition. Contents: Foreword. Preface. 1. Introduction. 2. Archaeological Excavations in Gujarat. 3. Conclusion. Appendices. Bibliography. Index. This book 'Excavations in Gujarat' gives a comprehensive history of excavated sites in Gujarat along with the material culture unearthed during excavations. These are otherwise unpublished and a many lies in the doctoral thesis of scholars that are unavailable to others. Gujarat is the only state in India where the archaeological vestiges has revealed the evidences for the first, second and third urbanizations. Besides, the study of the variety of small objects from excavation has helped in understanding the life of the common people which is of enduring interest. All this had added to our knowledge and understanding of the development of the personality of India. (jacket).…

Hardcover. Zustand: New. Mysore has a long and unique history, tangible and intangible heritage as also cultural traditions of its own. It is further augmented by its location in the vicinity of River Cauvery and its subsidiaries such as Hemavati, Shimsha, Suvarnamukhi, Arkavathi, etc. These rivers contributed to the evolution of cultures, continuously from prehistoric period to the modern times, making the region the cradle powerful kingdoms and cultures. Its composite, inclusive culture and peaceful co-existence are the hallmark from the ancient times through to the present day. With its historical monuments ranging from beautiful temples, excavated remains to glorious Islamic monuments, vernacular architecture to the imperial British structures, Mysore is an attractive tourist destination too. What started off as a casual discussion among us on the subject evolved in to serious academic exercise over the period of four years resulting in publication of this book. We have sincerely attempted to cover regional history, museum objects, art and cultural traditions. We have also tried to make it well illustrated. We hope the book will be useful for the serious researchers, students and equally for the tourists as well.…

Zustand: New. pp. 352.

Paperback. Zustand: 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.…

Zustand: New.

Hardcover. Zustand: New. 1st Edition. Contents: Foreword. Preface. 1. Introduction. 2. Review of the principal excavated sites. 3. Origin and chronology. 4. Architecture. 5. Pottery. 6. Stone tools and other objects of daily life. 7. Domestication of animals and plants. 8. Ashmount and its related problems. 9. Rock art. 10. Burial practices. 11. Conclusion. Bibliography. Index. The book Neolithic Cultures of South India deals with cultural changes and adaptations of the settled life in different stages of time span during the Neolithic period in South India. This particular book has many unique qualities like the South Indian Neolithic cultural sites are briefly documented based on the excavation reports. Being the field archaeologist the author very well used the various data available in the excavation reports to farm the conclusive results. Technological developments in the field of stone tools and other associated technologies such as metallurgy, stone and terracotta beads, development of pottery and its stages really attracts attention. In Origin and Chronology of the culture the methods he adopted is not based on hypothesis, but based on the scientific dating methods which speaks volumes on the authenticity of the facts. The book deals with all the aspects of the culture like disposal of the dead, domestication of the animals and plants, architecture and the aesthetic wisdom of the people in detail. This culture in South India is associated with ash mounds and it is briefly cited in this volume. In the Archaeological studies of Indian cultures such compilation and analysis is needed and this particular book faithfully fulfills the need of the hour in many respects. The photographs and drawings used in this book are original in nature. They enhance the quality of the presentation and it is worth to be possessed by anyone interested in the field of study. (jacket).…

Paperback. Zustand: 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.…

Zustand: New. pp.764 Illus.

Paperback. Zustand: New. 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 methods 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.…

Zustand: New. pp.764.

Contents Vol I Epigraphy 1 Brahmi script-its forgotten origin tracedS Sankaranarayanan 2 Uniqueness of Rudradama?s Girinagar Rock-edict Afresh appraisalRasesh Jamindar 3 Junnar-the Yajnabhumi of Siri Satakarni and NaganikaShobhana Gokhale 4 Bronze pedestal inscription of Hamlapuri RamtekPradip Shaligram Meshram and Dhiraj Yadavarao Choudhari 5 Priyavratavarma a new entrant into the early Kadamba genealogySG Samak 6 Buddhabhadra?s dedicatory inscription at Ajanta a reviewRajesh K Singh 7 A newly discovered early copper plate inscriptionShrinivas V Padigar 8 Epigraphical resources from Ta ProhmKM Bhadri 9 The date of the Ellora Plates of DantidurgaBrahmanand Deshpande 10 Nayagarh Copper plate grant of Satrubhanja TribhuvanakalasaBharati Pal 11 A Vigraha Grant discovered from BaragaonPK Nayak 12 A note on the Sarabhavaram plates of the Lord of CikuraC Somasundara Rao 13 Kadagodi inscription of Rajendra Cola IS Swaminathan 14 Traders guild at ManneHS Gopala Rao 15 Tamil kinship terms in Uttaramerur inscriptionsKR Shankaran 16 Recent epigraphical discoveries in Tamil NaduS Rajavelu 17 Alvayi inscription of the time of Calukya Vikramaditya VIDM Nagaraj 18 The Sangamesvara Temple Inscriptions at Kohalli Saka 1071Anant Kulkarni 19 Khajarapada Copper Plate charter of Danarnavadeva of Jhadakhanda-desaSnigdha Tripathi 20 A new inscription of Seuna Singhana IIAnand Kumbhar 21 Narahari-tirtha the Great Dvaita Saint and Pontiff; an epigraphical profileCV Ramachandra Rao 22 From Gosasa to Turugolo cattle economy trends in medieval KarnatakaRajaram Hegde 23 Some Nisidhi stones from the RayalsimaD Kiran Kranth Choudary 24 Epigraphs from the Palani Hills Tamil NaduRN Kumaran and M Saranya 25 Kasheli Marathi inscription of HaripaladevaHS Thosar 26 A new copper plate Grant of Silahara MallikarjunaSG Dhopate 27 Kadaparru Grant of VemaCA Padmanabha Sastry 28 A new inscription from Kakkehalli Udupi TalukPN Narasimhamurthy 29 Darpalli inscription of Recerla Pamnnamka Prabhu dated Saka 1375NS Ramachandra Murthy 30 Konasamudra Grant of AcyutarayaHM Nagarajarao 31 Lepaksi An epigraphical studySS Ramachandra Murthy 32 Unpublished Kogilehalli copper plate of VenkatapatirayaR Gopal and TS Gangadhara 33 Ethno-cultural profile of Vipravinodins-an epigraphical reflectionS Smitha 34 Languages used in Indian inscriptions a surveyMadhav N Katti 35 Wells as known from epigraphsJaiprakash 36 Three Persian epigraphs of Nawab of Arcot from Gingee Fort Tamil NaduGS Khwaja 37 Recent discoveries and re-examination of Arabic and Persian Inscriptions from Haryana and PunjabSS Hussain 38 A rare document of Tippu and Shaik AyazKeladi Venkatesh Jois 39 Inscriptions on ancient Indian medical history with reference to KarnatakaKG Vasantha Madhava 40 Two inscriptions bearing on the Citra-Mantapa in MysoreRH Kulkarni 41 An inscription from Elavanasur and a woman BodyguardK Karuppiah 42 Virabhadra in Vijayanagara inscriptionsMV Vishweshwara and CB Patil 43 Literary study of a Sanskrit inscription from HanumakondaKeyur R Karagudari 44 Pasupatas and Kalamukhas their affiliations to PariseBV ShirurVol II History 45 Candragupta I-the first Maharajadhiraja of the imperial Gupta dynasty an historical reconstructKiran Kumar Thaplyal 46 A note on the Pallava subordinate VayirameganS Srinivasan 47 The Sendrakas an early Jaina familyHampa Nagarajaiah 48 Academic activity in early AndhraPV Parabrahma Sastry 49 Konerinmaikondan the matchless kingY Subbarayalu 50 Early maritime trade in South India some considerations on native tradersP Shanmugam 52 Economic conditions of Uttara Kannada region in the historical periodKG Bhatsoori 53 The difference in the padikaval practice between Pudukkottai District and northern Tamil districts during the thirteenth centuryNoboru Karashima 54 Inscriptions of India and Southeast Asia through the Ancient and Early medieval periodsKV Ramesh 55 From Prosperity to Poverty-A case of water culture interface in Monsoon AsiaS Nagaraju 56 Maritime contacts of Karnat. 146 plates (illustrator).…