Norman yates (24 Ergebnisse)

Soft cover. Zustand: Very Good+. Zustand des Schutzumschlags: coNo Jacket. 1st Edition. This is a privately published stapled booklet of historical photos compiled by the Potton Historical Society. All photos have captions. A couple of light marks on the glossy front cover, pages bright and white with no creases, tears or names. No page numbers, and no date, but circa 1977. A nice slice of local history that in years to come will be long out of print and impossible to find. This one is in great condition! None of my books are ex-library, remainders or bce unless specified. Photos by Vera and Norman Parry (illustrator).…

Soft cover. Zustand: NF. This is a high-quality commercial reprint of the one sheet which measures 11X17. This reprint comes with a cardboard backing board and in a sealed outer bag. Great for gift giving or framing. Size: 11" x 17". Poster.

Zustand: Good.

PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

Pamphlet. Zustand: Near Fine Plus. First Edition. Squarish, 8" x 8", printed on glossy cardstock, 8 pages counting the covers. Incudes reproduction of five drawings from the exhibition. Postage will be reduced for this item. Exhibition Catalogue.

Thin Trade Paperback. Zustand: Very Good. First Edition. Minor wear to cover edges and 5 numbers, in ink, written top of front cover. Contributions by Pierre Falcon, Frederick Candelaria, Jon Whyte, Christopher Wiseman and Leona Gom. Literary Periodical.

Softcover. Zustand: Gut. XVIII,217 S. m. 81 Abb., kt. - FAO Agricultural Development Paper;94 - Bibl.-Ex.

Softcover. Zustand: Good. First Edition. 45 p. 24 cm. 10 partial colour illustratins. Black card covers in attached grey jacket. Some discolouration to top edges and stain on bottom front corner. Autographed by author on first leaf.

Card Covers. Zustand: Very Good Condition. Zustand des Schutzumschlags: No Dust Jacket. As Issued. Bright Orange and yellowe illustrated card cover. Content clean, bright and sound. No faults. Cover By Norman Yates (illustrator).

Paperback. Zustand: Good. No Dustjacket. Later Edition. ISBN . B0017KLP4W Trade Paperback. Good Condition. Tight sound unmarked copy with rubs to front cover, sticker on back cover, evidence of neatly done glue repair, rubs to rubs to edges and corners of covers. No statement of later printing on copyright page. No Signature.…

[NONE] 1976. (Mass market paperback) Near fine. NP. 8vo. Gallery catalogue by exhibtion of the same name, first shown at the Edmonton Art Gallery, Edmonton, Alberta from November 19 - December 17, 1976. The exhibtion then travelled around Canada with shows in Swift Current, SK, Calgary, AB, Montreal, QC, Charlottetown, PE, Fredericto, NB, and Halifax, NS. White card covers, stapled; front illustrated / Landscape Seventeen (1976). Colour, as well as black and white plates. Clean, crisp, bright. …

[0-88864-963-0] 1983. (Mass market paperback) Very good. 82pp. 12mo. Gallery catalogue, published for the retrospective exhibition held at the Ring House Gallery in August-September, 1983. Illustrated card covers; colour, and black and white illustrations. Clean and crisp.

Hardcover with dustjacket, 144 pages; as new condition; clean and crisp; no internal marks. Foreign shipping may be extra.

Pamphlet. Zustand: Good. volume 2, no 5, November 1965 (whole number 11) cover chipped, detached, pages clean and tight. Contents: Edward D. Hoch - The Empty Zoo.--Ambrose Bierce - A Psychological Shipwreck.--Laurence Manning - The Call Of The Mech-Men.--Guy De Maupassant - Was It A Dream.--Katherine Yates - Under The Hau Tree.--Robert E. Howard - Rattle Of Bones.--Dorothy Norman Cooke - The Head Of Du Bois.--Robert E. Howard - The Dweller In The Dark Valley (verse).--Greye La Spina - The Devil's Pool.…

Soft cover. Zustand: Very Good. 7.5" x 9". 82 pp. Catalogue that accompanied the exhibition. Illustrated. Bright clean copy. Covers have some light shelf wear, bottom corners slightly curled.

Zustand: Very Good. No Dj. 8vo pp. 5 82, colour illustrations, published in conjunction with a retrospective exhibition held at the Ring House Gallery in August 1983. book.

Taschenbuch. Zustand: Neu. Neuware - Are you serious about breaking into data science or AI - but tired of scattered tutorials, half-finished courses, and 'learn Python in 24 hours' promises This book gives you something different: a complete, structured, 14-week university-level curriculum - from Python fundamentals to building and deploying LLM-powered AI applications - without a $60,000 master's program.Modeled on graduate-level coursework. Designed for self-directed learners.Every week is structured like a university class: - Clear learning objectives (what you will actually be able to do)- Curated readings from leading textbooks and free online resources- A real, graded-style assignment that produces a portfolio artifact- The tools and libraries professionals use on the jobNo filler. No hand-holding. Just the program.WHAT YOU WILL COVER: Phase 1 - Foundations (Weeks 1-3): Python, NumPy, mathematics for ML (linear algebra, calculus, probability), and exploratory data analysis with Pandas.Phase 2 - Data Engineering and Visualization (Weeks 4-5): SQL through window functions, ETL pipeline design, data cleaning, and interactive dashboards with Plotly and Streamlit.Phase 3 - Machine Learning (Weeks 6-9): Supervised learning, feature engineering, model interpretation with SHAP, clustering, and dimensionality reduction.Phase 4 - Deep Learning (Weeks 10-11): Neural networks from scratch, backpropagation, PyTorch, CNNs, RNNs, and transfer learning.Phase 5 - Applied AI (Weeks 12-13): How LLMs work, prompt engineering, retrieval-augmented generation (RAG), agentic AI, and production AI applications.Phase 6 - Capstone (Week 14): A GitHub repository, technical research report, live deployed demo, and recorded presentation.WHO THIS IS FOR: - Career changers wanting a structured path into data science or AI- Software engineers moving into ML and AI roles- Analysts who want to go deeper into modeling and AI- Recent graduates wanting a rigorous supplement to their degree- Self-taught programmers tired of jumping between resourcesPrerequisites: Basic programming experience, high school algebra, willingness to do the work. No prior data science knowledge required.BY THE END OF WEEK 14, YOU WILL: - Build and deploy production-ready ML models end-to-end- Design and fine-tune deep learning architectures- Build LLM-powered applications with RAG, agents, and tool use- Communicate findings through professional data visualizations- Present a complete capstone portfolio project to a technical audienceStop collecting courses. Start finishing one.…

23 x 15. 217 Seiten. Mit zahlreichen Abbildungen. Obrosch. Ordnungsgemäß aus einer Universitäts-Bibliothek ausgesondertes Exemplar (Stempel, Klebereste Rückenschild). Einbandkanten etwas berieben, sonst sehr guter Zustand. Sprache: Englisch Gewicht in Gramm: 400.

Exhibition catalogue. 200x250mm 20 pages stapled catalogue. Illustrated in black and white and colour. Card covers. Very good. We are specialists in Catalogues: Exhibitions, Auctions, Collections, etc., with a picture of the cover available on request. All items are as described and dispatched within 36 hours in a secure package. We are professional booksellers with over 30 years experience and a real-life bookshop. You may order with confidence.…

Paperback. Zustand: new. Paperback. Are you serious about breaking into data science or AI - but tired of scattered tutorials, half-finished courses, and "learn Python in 24 hours" promises?This book gives you something different: a complete, structured, 14-week university-level curriculum - from Python fundamentals to building and deploying LLM-powered AI applications - without a $60,000 master's program.Modeled on graduate-level coursework. Designed for self-directed learners.Every week is structured like a university class: Clear learning objectives (what you will actually be able to do)Curated readings from leading textbooks and free online resourcesA real, graded-style assignment that produces a portfolio artifactThe tools and libraries professionals use on the jobNo filler. No hand-holding. Just the program.WHAT YOU WILL COVER: Phase 1 - Foundations (Weeks 1-3): Python, NumPy, mathematics for ML (linear algebra, calculus, probability), and exploratory data analysis with Pandas.Phase 2 - Data Engineering and Visualization (Weeks 4-5): SQL through window functions, ETL pipeline design, data cleaning, and interactive dashboards with Plotly and Streamlit.Phase 3 - Machine Learning (Weeks 6-9): Supervised learning, feature engineering, model interpretation with SHAP, clustering, and dimensionality reduction.Phase 4 - Deep Learning (Weeks 10-11): Neural networks from scratch, backpropagation, PyTorch, CNNs, RNNs, and transfer learning.Phase 5 - Applied AI (Weeks 12-13): How LLMs work, prompt engineering, retrieval-augmented generation (RAG), agentic AI, and production AI applications.Phase 6 - Capstone (Week 14): A GitHub repository, technical research report, live deployed demo, and recorded presentation.WHO THIS IS FOR: Career changers wanting a structured path into data science or AISoftware engineers moving into ML and AI rolesAnalysts who want to go deeper into modeling and AIRecent graduates wanting a rigorous supplement to their degreeSelf-taught programmers tired of jumping between resourcesPrerequisites: Basic programming experience, high school algebra, willingness to do the work. No prior data science knowledge required.BY THE END OF WEEK 14, YOU WILL: Build and deploy production-ready ML models end-to-endDesign and fine-tune deep learning architecturesBuild LLM-powered applications with RAG, agents, and tool useCommunicate findings through professional data visualizationsPresent a complete capstone portfolio project to a technical audienceStop collecting courses. Start finishing one. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Zustand: New. Print on Demand.

Hardcover. Zustand: Very Good. Zustand des Schutzumschlags: No Jacket, as issued. LIMITED EDITION. Oblong 8vo. LIMITED SIGNED EDITION, number 9 out of 150 deluxe copies (of 576 total), SIGNED by listed contributors including Stephen King. Light edgewear to covers. Slight fading to cloth binding. Minor soiling to covers. Light blue pen mark to front cover near spine. Pencil ghost to first blank page. Slight fraying to cloth binding on rear cover near spine. Fading with slight soiling to slipcase. Red pen stain to rear panel of slipcase in middle of panel. Slight rubbing and fading to slipcase. Slight fraying to top and bottom edge of slipcase. Fading and rubbing to spine of slipcase. VG in VG slipcase. …

Paperback. Zustand: new. Paperback. Are you serious about breaking into data science or AI - but tired of scattered tutorials, half-finished courses, and "learn Python in 24 hours" promises?This book gives you something different: a complete, structured, 14-week university-level curriculum - from Python fundamentals to building and deploying LLM-powered AI applications - without a $60,000 master's program.Modeled on graduate-level coursework. Designed for self-directed learners.Every week is structured like a university class: Clear learning objectives (what you will actually be able to do)Curated readings from leading textbooks and free online resourcesA real, graded-style assignment that produces a portfolio artifactThe tools and libraries professionals use on the jobNo filler. No hand-holding. Just the program.WHAT YOU WILL COVER: Phase 1 - Foundations (Weeks 1-3): Python, NumPy, mathematics for ML (linear algebra, calculus, probability), and exploratory data analysis with Pandas.Phase 2 - Data Engineering and Visualization (Weeks 4-5): SQL through window functions, ETL pipeline design, data cleaning, and interactive dashboards with Plotly and Streamlit.Phase 3 - Machine Learning (Weeks 6-9): Supervised learning, feature engineering, model interpretation with SHAP, clustering, and dimensionality reduction.Phase 4 - Deep Learning (Weeks 10-11): Neural networks from scratch, backpropagation, PyTorch, CNNs, RNNs, and transfer learning.Phase 5 - Applied AI (Weeks 12-13): How LLMs work, prompt engineering, retrieval-augmented generation (RAG), agentic AI, and production AI applications.Phase 6 - Capstone (Week 14): A GitHub repository, technical research report, live deployed demo, and recorded presentation.WHO THIS IS FOR: Career changers wanting a structured path into data science or AISoftware engineers moving into ML and AI rolesAnalysts who want to go deeper into modeling and AIRecent graduates wanting a rigorous supplement to their degreeSelf-taught programmers tired of jumping between resourcesPrerequisites: Basic programming experience, high school algebra, willingness to do the work. No prior data science knowledge required.BY THE END OF WEEK 14, YOU WILL: Build and deploy production-ready ML models end-to-endDesign and fine-tune deep learning architecturesBuild LLM-powered applications with RAG, agents, and tool useCommunicate findings through professional data visualizationsPresent a complete capstone portfolio project to a technical audienceStop collecting courses. Start finishing one. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…