James burridge (38 risultati)

Soft cover. Condizione: Fine. 8pp Artist exhibition catalogue. 27 art works listed with a small selection illus. James Burridge (illustratore).

Soft cover. Condizione: Good / Very Good. First Paperback Ed. & 1st Printing.. My Fathers Return by Donald Campbell; What Does Your Name Mean?; Atlantis- When did it Vanish? ** ARTICLES AND STORIES (1) My Dead Fathers Return by Fred Archer (2) Is Your Name You? By Charles James (3) Atlantis When did it disappear? By H.C. Goble (4) Does the Devil Live Here? By Wally George (5) Prophecy for Napoleon by Fred Korotkin (6) What was John Keelys Discovery? By Gaston Burridge (7) Voices in the Wind? Frank Edwards (8) And the World Lost its Greatest Wonder! By Curtis Fuller (9) Honour to the old gods by G.B.Spencer >> Cover scuffing; crease to backcover. Size: 12mo - over 6¾" - 7¾" tall. Book.…

Condizione: Acceptable. Readable, but has significant damage / tears. Has a remainder mark. paperback Used - Acceptable 2026.

Softcover. Condizione: Excellent condition. xx, 407 pp. GlossaHouse Festschrift Series. Volume 1. Softcover. LCC: 2017956474.

Softcover. Condizione: Excellent condition. xx, 407 pp. GlossaHouse Festschrift Series. Volume 1. Softcover. LCC: 2017956474.

Softcover. Condizione: Excellent condition. xx, 407 pp. GlossaHouse Festschrift Series. Volume 1. Softcover. LCC: 2017956474.

Paperback or Softback. Condizione: New. Inference in Statistical Modelling and Machine Learning. Book.

Paperback. Condizione: New. Statistical modelling and machine learning offer a vast toolbox of inference methods with which to model the world, discover patterns and reach beyond the data to make predictions when the truth is not certain. This concise book provides a clear introduction to those tools and to the core ideas - probabilistic model, likelihood, prior, posterior, overfitting, underfitting, cross-validation - that unify them. Toy and real examples illustrate diverse applications ranging from biomedical data to treasure hunts, while the accompanying datasets and computational notebooks in R and Python encourage hands-on learning. Instructors can benefit from online lecture slides and solutions to all the exercises. Requiring only first-year university-level knowledge of calculus, probability and linear algebra, the book equips students in statistics, data science and machine learning, as well as those in quantitative applied and social science programmes, with the tools and conceptual foundations to explore more advanced techniques.…

Condizione: New.

Paperback. Condizione: New. Statistical modelling and machine learning offer a vast toolbox of inference methods with which to model the world, discover patterns and reach beyond the data to make predictions when the truth is not certain. This concise book provides a clear introduction to those tools and to the core ideas - probabilistic model, likelihood, prior, posterior, overfitting, underfitting, cross-validation - that unify them. Toy and real examples illustrate diverse applications ranging from biomedical data to treasure hunts, while the accompanying datasets and computational notebooks in R and Python encourage hands-on learning. Instructors can benefit from online lecture slides and solutions to all the exercises. Requiring only first-year university-level knowledge of calculus, probability and linear algebra, the book equips students in statistics, data science and machine learning, as well as those in quantitative applied and social science programmes, with the tools and conceptual foundations to explore more advanced techniques.…

Condizione: New. 2026. paperback. . . . . .

Paperback / softback. Condizione: New. New copy - Usually dispatched within 3 working days.

Condizione: New. 2026. paperback. . . . . . Books ship from the US and Ireland.

Paperback. Condizione: Brand New. 323 pages. 7.00x0.67x10.00 inches. In Stock.

Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - Statistical modelling and machine learning offer a vast toolbox of inference methods with which to model the world, discover patterns and reach beyond the data to make predictions when the truth is not certain. This concise book provides a clear introduction to those tools and to the core ideas - probabilistic model, likelihood, prior, posterior, overfitting, underfitting, cross-validation - that unify them. Toy and real examples illustrate diverse applications ranging from biomedical data to treasure hunts, while the accompanying datasets and computational not Elektronisches Buch in R and Python encourage hands-on learning. Instructors can benefit from online lecture slides and solutions to all the exercises. Requiring only first-year university-level knowledge of calculus, probability and linear algebra, the book equips students in statistics, data science and machine learning, as well as those in quantitative applied and social science programmes, with the tools and conceptual foundations to explore more advanced techniques.…

Paperback. Condizione: new. Paperback. Statistical modelling and machine learning offer a vast toolbox of inference methods with which to model the world, discover patterns and reach beyond the data to make predictions when the truth is not certain. This concise book provides a clear introduction to those tools and to the core ideas probabilistic model, likelihood, prior, posterior, overfitting, underfitting, cross-validation that unify them. Toy and real examples illustrate diverse applications ranging from biomedical data to treasure hunts, while the accompanying datasets and computational notebooks in R and Python encourage hands-on learning. Instructors can benefit from online lecture slides and solutions to all the exercises. Requiring only first-year university-level knowledge of calculus, probability and linear algebra, the book equips students in statistics, data science and machine learning, as well as those in quantitative applied and social science programmes, with the tools and conceptual foundations to explore more advanced techniques. This concise introduction to statistical modelling and machine learning focuses on core ideas and a carefully selected set of representative methods. Requiring only introductory calculus, probability and linear algebra, it provides readers with an immediately useful toolkit and equips them to consult more advanced resources. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Paperback. Condizione: New. Statistical modelling and machine learning offer a vast toolbox of inference methods with which to model the world, discover patterns and reach beyond the data to make predictions when the truth is not certain. This concise book provides a clear introduction to those tools and to the core ideas - probabilistic model, likelihood, prior, posterior, overfitting, underfitting, cross-validation - that unify them. Toy and real examples illustrate diverse applications ranging from biomedical data to treasure hunts, while the accompanying datasets and computational notebooks in R and Python encourage hands-on learning. Instructors can benefit from online lecture slides and solutions to all the exercises. Requiring only first-year university-level knowledge of calculus, probability and linear algebra, the book equips students in statistics, data science and machine learning, as well as those in quantitative applied and social science programmes, with the tools and conceptual foundations to explore more advanced techniques.…

Paperback. Condizione: New. Statistical modelling and machine learning offer a vast toolbox of inference methods with which to model the world, discover patterns and reach beyond the data to make predictions when the truth is not certain. This concise book provides a clear introduction to those tools and to the core ideas - probabilistic model, likelihood, prior, posterior, overfitting, underfitting, cross-validation - that unify them. Toy and real examples illustrate diverse applications ranging from biomedical data to treasure hunts, while the accompanying datasets and computational notebooks in R and Python encourage hands-on learning. Instructors can benefit from online lecture slides and solutions to all the exercises. Requiring only first-year university-level knowledge of calculus, probability and linear algebra, the book equips students in statistics, data science and machine learning, as well as those in quantitative applied and social science programmes, with the tools and conceptual foundations to explore more advanced techniques.…

Condizione: New.

Hardback. Condizione: New. Statistical modelling and machine learning offer a vast toolbox of inference methods with which to model the world, discover patterns and reach beyond the data to make predictions when the truth is not certain. This concise book provides a clear introduction to those tools and to the core ideas - probabilistic model, likelihood, prior, posterior, overfitting, underfitting, cross-validation - that unify them. Toy and real examples illustrate diverse applications ranging from biomedical data to treasure hunts, while the accompanying datasets and computational notebooks in R and Python encourage hands-on learning. Instructors can benefit from online lecture slides and solutions to all the exercises. Requiring only first-year university-level knowledge of calculus, probability and linear algebra, the book equips students in statistics, data science and machine learning, as well as those in quantitative applied and social science programmes, with the tools and conceptual foundations to explore more advanced techniques.…

Condizione: New. 2026. hardcover. . . . . .

Hardcover. Condizione: Brand New. 323 pages. 7.00x0.75x10.00 inches. In Stock.

Condizione: New. 2026. hardcover. . . . . . Books ship from the US and Ireland.

Condizione: New.

Buch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - Statistical modelling and machine learning offer a vast toolbox of inference methods with which to model the world, discover patterns and reach beyond the data to make predictions when the truth is not certain. This concise book provides a clear introduction to those tools and to the core ideas - probabilistic model, likelihood, prior, posterior, overfitting, underfitting, cross-validation - that unify them. Toy and real examples illustrate diverse applications ranging from biomedical data to treasure hunts, while the accompanying datasets and computational not Elektronisches Buch in R and Python encourage hands-on learning. Instructors can benefit from online lecture slides and solutions to all the exercises. Requiring only first-year university-level knowledge of calculus, probability and linear algebra, the book equips students in statistics, data science and machine learning, as well as those in quantitative applied and social science programmes, with the tools and conceptual foundations to explore more advanced techniques.…

Hardback. Condizione: New. Statistical modelling and machine learning offer a vast toolbox of inference methods with which to model the world, discover patterns and reach beyond the data to make predictions when the truth is not certain. This concise book provides a clear introduction to those tools and to the core ideas - probabilistic model, likelihood, prior, posterior, overfitting, underfitting, cross-validation - that unify them. Toy and real examples illustrate diverse applications ranging from biomedical data to treasure hunts, while the accompanying datasets and computational notebooks in R and Python encourage hands-on learning. Instructors can benefit from online lecture slides and solutions to all the exercises. Requiring only first-year university-level knowledge of calculus, probability and linear algebra, the book equips students in statistics, data science and machine learning, as well as those in quantitative applied and social science programmes, with the tools and conceptual foundations to explore more advanced techniques.…

[1] pp.; 35.4 x 21.5 cm.; loose leaves; black-and-white; edition size unknown; unsigned and unnumbered; offset-printed Program for 24 hour performances held during the 5th Annual New York Avant Garde Festival presented by Charlotte Moorman in cooperation with the New York City Department of Marine and Aviation, September 29 - 30, 1967. Performers included Charlotte Moorman, Ay-o, Robert Breer, Robert Burridge, Christo, Ellen Chuse, Philip Corner, Ken Dewey, Bill Dixon, Judith Dunn, Charles Frazier, Jimmy Giuffre, Malcolm Goldstein, Don Heckman, Al Hansen, Gary Harris, Geoffrey Hendricks, Bici Hendricks, Dick Hogle, Takehiko Iimura, Ken Jacobs, Ray Johnson, Sheila Jordan, Allan Kaprow, Robin Kenyatta, Takehisa Kosugi, Jackson MacLow, Carol Marcy, Max V. Mathews, James H. McWilliams, Marta Minujin, Max Neuhaus, Ralph Ortiz, Nam June Paik, Lil Picard, Sun Ra, Ely Raman, Steve Rettew, Carolee Schneemann, Michael Snow, Ed Summerlin, Cecil Taylor, James Tenney, Jean Toche, Uni-Trio, USCO, John Van Saun, Frank Lincoln Viner, Bob Watts, and Jud Yalkut performing works by dozens of artists including John Cage, Chieko Shiomi, Joseph Beuys, La Monte Young and many others. Fair. Folded in eight. Extensive handling wear with overall creasing and crinkling of the page. 6 mm. dog-ear to upper right corner and 12.7 cm. dog-ear to upper left corner. 2 cm. rip at bottom edge of sheet along fold.…

[1] pp.; 35.4 x 21.5 cm.; loose leaves; black-and-white; edition size unknown; unsigned and unnumbered; offset-printed Program for 24 hour performances held during the 5th Annual New York Avant Garde Festival presented by Charlotte Moorman in cooperation with the New York City Department of Marine and Aviation, September 29 - 30, 1967. Performers included Charlotte Moorman, Ay-o, Robert Breer, Robert Burridge, Christo, Ellen Chuse, Philip Corner, Ken Dewey, Bill Dixon, Judith Dunn, Charles Frazier, Jimmy Giuffre, Malcolm Goldstein, Don Heckman, Al Hansen, Gary Harris, Geoffrey Hendricks, Bici Hendricks, Dick Hogle, Takehiko Iimura, Ken Jacobs, Ray Johnson, Sheila Jordan, Allan Kaprow, Robin Kenyatta, Takehisa Kosugi, Jackson MacLow, Carol Marcy, Max V. Mathews, James H. McWilliams, Marta Minujin, Max Neuhaus, Ralph Ortiz, Nam June Paik, Lil Picard, Sun Ra, Ely Raman, Steve Rettew, Carolee Schneemann, Michael Snow, Ed Summerlin, Cecil Taylor, James Tenney, Jean Toche, Uni-Trio, USCO, John Van Saun, Frank Lincoln Viner, Bob Watts, and Jud Yalkut performing works by dozens of artists including John Cage, Chieko Shiomi, Joseph Beuys, La Monte Young and many others. Good. Folded in eight with light edge-wear, a 6 mm. ink mark on recto and 2 cm. area of light yellow soiling.…

Paperback. Condizione: new. Paperback. Statistical modelling and machine learning offer a vast toolbox of inference methods with which to model the world, discover patterns and reach beyond the data to make predictions when the truth is not certain. This concise book provides a clear introduction to those tools and to the core ideas probabilistic model, likelihood, prior, posterior, overfitting, underfitting, cross-validation that unify them. Toy and real examples illustrate diverse applications ranging from biomedical data to treasure hunts, while the accompanying datasets and computational notebooks in R and Python encourage hands-on learning. Instructors can benefit from online lecture slides and solutions to all the exercises. Requiring only first-year university-level knowledge of calculus, probability and linear algebra, the book equips students in statistics, data science and machine learning, as well as those in quantitative applied and social science programmes, with the tools and conceptual foundations to explore more advanced techniques. This concise introduction to statistical modelling and machine learning focuses on core ideas and a carefully selected set of representative methods. Requiring only introductory calculus, probability and linear algebra, it provides readers with an immediately useful toolkit and equips them to consult more advanced resources. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Paperback. Condizione: Brand New. 323 pages. 7.00x0.67x10.00 inches. In Stock. This item is printed on demand.