00915nam0-22003131i-450 99000176896040332120190529131408.0000176896FED01000176896(Aleph)000176896FED0100017689620030910d1971----km-y0itay50------baita<<La >>coltivazione del peperone e della melanzana in ambiente protettoPietro CarusoCatania[s.n.]197118 p.24 cmEstr. da: Tecnica agricola, 23(2),1971.PeperoniMelanzane635.643635.646Caruso,Pietro72495ITUNINARICAUNIMARCLG99000176896040332160 OP. 86/3143082FAGBCFAGBCColtivazione del peperone e della melanzana in ambiente protetto363968UNINA04159nam 2200613 450 991081654340332120230803221153.01-4625-1570-31-4625-1569-X(CKB)2550000001265994(EBL)1673310(OCoLC)876901395(SSID)ssj0001193776(PQKBManifestationID)11681727(PQKBTitleCode)TC0001193776(PQKBWorkID)11149868(PQKB)10588800(MiAaPQ)EBC1673310(EXLCZ)99255000000126599420140511h20142014 uy 0engur|n|---|||||txtccrThe common core coaching book strategies to help teachers address the K-5 ELA standards /Laurie Elish-Piper and Susan K. L'AllierNew York, New York :The Guilford Press,2014.©20141 online resource (242 p.)Teaching Practices That WorkDescription based upon print version of record.1-4625-1557-6 1-306-58403-5 Includes bibliographical references and index.Cover; Half Title Page; Series Page; Title Page; Copyright Page; About the Authors; Series Editors' Note; Acknowledgments; Contents; Part One. Coaching toward the Common Core; 1. Getting Ready for Coaching; 2. Tools for Effective Coaching; Part Two. Large-Group Coaching toward the Common Core; Strategy 1. Establishing a Climate for Literacy Coaching; Strategy 2. Building Shared Understanding and Language; Strategy 3. Conducting an Article Study Group; Strategy 4. Providing Professional Development at Faculty Meetings; Strategy 5. Unpacking the Common Core StandardsStrategy 6. Examining the Vertical Alignment of the Common Core StandardsStrategy 7. Presenting Powerful Professional Development; Part Three. Small-Group Coaching toward the Common Core; Strategy 8. Developing Implementation Guides for the Common Core Standards; Strategy 9. Reviewing Assessment Data to Plan Instruction; Strategy 10. Examining Student Work; Strategy 11. Reviewing Units of Study; Strategy 12. Conducting a Lesson Study; Part Four. Individual Coaching toward the Common Core; Strategy 13. Setting Goals; Strategy 14. Modeling; Strategy 15. Co-Planning; Strategy 16. Co-TeachingStrategy 17. ObservingStrategy 18. Implementing the Coaching Cycle; Part Five. Putting It All Together: Profiles of Highly Effective Literacy Coaches; Profile 1. Establishing and Maintaining Administrator Support; Profile 2. Getting into Classrooms; Profile 3. Working with Hesitant Teachers; Profile 4. Staying the Course; Profile 5. Embedding Coaching into Other Assigned Duties; Profile 6. Organizing for Success; Final Thoughts; References; Index This book provides essential coaching tools to support teachers in planning and implementing instruction aligned with the Common Core State Standards (CCSS). The authors explain the key instructional shifts brought about by the CCSS in K-5 English language arts classrooms. Eighteen specific strategies for coaching large groups, small groups, and individual teachers are presented, including clear-cut procedures, vivid illustrative examples, and 28 reproducible forms. Grounded in research on adult learning, the book addresses common coaching challenges and how to overcome them. The large-Teaching practices that work.Language arts (Elementary)StandardsUnited StatesLanguage arts (Elementary)Activity programsUnited StatesLanguage arts (Elementary)StandardsLanguage arts (Elementary)Activity programs372.6LAN010000EDU032000LAN013000EDU029020EDU046000bisacshElish-Piper Laurie1643329L'Allier Susan K.MiAaPQMiAaPQMiAaPQBOOK9910816543403321The common core coaching book4083443UNINA01028nam0 22002771i 450 UON0030556820231205104030.22096-350-6613-920071212d2005 |0itac50 bahunHU|||| 1||||ˆAz ‰en színreviteleÖnéletírás a 20. századi magyar irodalombanDobos IstvanBudapestBalassi Kiado2005279 p.24 cm.Letteratura unghereseAutobiografieUONC068149FIHUBudapestUONL000090894.511Letteratura ungherese21DobosIstvanUONV176955696666Balassi KiadoUONV274236650ITSOL20251003RICASIBA - SISTEMA BIBLIOTECARIO DI ATENEOUONSIUON00305568SIBA - SISTEMA BIBLIOTECARIO DI ATENEOSI C 0293 SI EO 40479 5 0293 En színrevitele1378029UNIOR04086nam 22006855 450 991074628400332120251008152004.03-031-35114-210.1007/978-3-031-35114-3(MiAaPQ)EBC30751909(Au-PeEL)EBL30751909(DE-He213)978-3-031-35114-3(PPN)272737526(CKB)28284169000041(EXLCZ)992828416900004120230922d2023 u| 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierMachine Learning for Earth Sciences Using Python to Solve Geological Problems /by Maurizio Petrelli1st ed. 2023.Cham :Springer International Publishing :Imprint: Springer,2023.1 online resource (xvi, 209 pages) illustrationsSpringer Textbooks in Earth Sciences, Geography and Environment,2510-1315Print version: Petrelli, Maurizio Machine Learning for Earth Sciences Cham : Springer International Publishing AG,c2023 9783031351136 Includes bibliographical references.Part 1: Basic Concepts of Machine Learning for Earth Scientists -- Chapter 1. Introduction to Machine Learning -- Chapter 2. Setting Up your Python Environments for Machine Learning -- Chapter 3. Machine Learning Workflow -- Part 2: Unsupervised Learning -- Chapter 4. Unsupervised Machine Learning Methods -- Chapter 5. Clustering and Dimensionality Reduction in Petrology -- Chapter 6. Clustering of Multi-Spectral Data -- Part 3: Supervised Learning -- Chapter 7. Supervised Machine Learning Methods -- Chapter 8. Classification of Well Log Data Facies by Machine Learning -- Chapter 9. Machine Learning Regression in Petrology -- Part 4: Scaling Machine Learning Models -- Chapter 10. Parallel Computing and Scaling with Dask -- Chapter 11. Scale Your Models in the Cloud -- Part 5: Next Step: Deep Learning -- Chapter 12. Introduction to Deep Learning.This textbook introduces the reader to Machine Learning (ML) applications in Earth Sciences. In detail, it starts by describing the basics of machine learning and its potentials in Earth Sciences to solve geological problems. It describes the main Python tools devoted to ML, the typical workflow of ML applications in Earth Sciences, and proceeds with reporting how ML algorithms work. The book provides many examples of ML application to Earth Sciences problems in many fields, such as the clustering and dimensionality reduction in petro-volcanological studies, the clustering of multi-spectral data, well-log data facies classification, and machine learning regression in petrology. Also, the book introduces the basics of parallel computing and how to scale ML models in the cloud. The book is devoted to Earth Scientists, at any level, from students to academics and professionals.Springer Textbooks in Earth Sciences, Geography and Environment,2510-1315Earth sciencesMachine learningArtificial intelligenceMathematicsApplication softwareEarth SciencesMachine LearningArtificial IntelligenceApplications of MathematicsComputer and Information Systems ApplicationsEarth sciences.Machine learning.Artificial intelligence.Mathematics.Application software.Earth Sciences.Machine Learning.Artificial Intelligence.Applications of Mathematics.Computer and Information Systems Applications.550.028557Petrelli Maurizio1024610MiAaPQMiAaPQMiAaPQBOOK9910746284003321Machine Learning for Earth Sciences3568953UNINA