Isbn: 9780262546379 - the little learner: a straight line to deep learning (12 Ergebnisse)

PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000. Su, Qingqing (illustrator).

Zustand: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide. Su, Qingqing (illustrator).

Paperback. Zustand: Brand New. 436 pages. 9.00x7.00x1.06 inches. In Stock. Su, Qingqing (illustrator).

Zustand: New. Su, Qingqing (illustrator).

Zustand: New. In English. Su, Qingqing (illustrator).

Zustand: New. 2023. Paperback. . . . . . Books ship from the US and Ireland. Su, Qingqing (illustrator).

Zustand: NEW. Su, Qingqing (illustrator).

Kartoniert / Broschiert. Zustand: New. Daniel P. Friedman is Professor of Computer Science in the School of Informatics, Computing, and Engineering at Indiana University and is the author of many books published by the MIT Press, including The Little Schemer and The Seasoned Sch. Su, Qingqing (illustrator).…

Taschenbuch. Zustand: Neu. Neuware - A highly accessible, step-by-step introduction to deep learning, written in an engaging, question-and-answer style.The Little Learner introduces deep learning from the bottom up, inviting students to learn by doing. With the characteristic humor and Socratic approach of classroom favorites The Little Schemer and The Little Typer, this kindred text explains the workings of deep neural networks by constructing them incrementally from first principles using little programs that build on one another. Starting from scratch, the reader is led through a complete implementation of a substantial application: a recognizer for noisy Morse code signals. Example-driven and highly accessible, The Little Learner covers all of the concepts necessary to develop an intuitive understanding of the workings of deep neural networks, including tensors, extended operators, gradient descent algorithms, artificial neurons, dense networks, convolutional networks, residual networks, and automatic differentiation. - Conversational style, illustrations, and question-and-answer format make deep learning accessible and fun- Incremental approach constructs advanced concepts from first principles- Presents key ideas of machine learning using a small, manageable subset of the Scheme language- Suitable for anyone with knowledge of high school math and some programming experience. Su, Qingqing (illustrator).…

Taschenbuch. Zustand: Neu. Neuware -A highly accessible, step-by-step introduction to deep learning, written in an engaging, question-and-answer style.The Little Learner introduces deep learning from the bottom up, inviting students to learn by doing. With the characteristic humor and Socratic approach of classroom favorites The Little Schemer and The Little Typer, this kindred text explains the workings of deep neural networks by constructing them incrementally from first principles using little programs that build on one another. Starting from scratch, the reader is led through a complete implementation of a substantial application: a recognizer for noisy Morse code signals. Example-driven and highly accessible, The Little Learner covers all of the concepts necessary to develop an intuitive understanding of the workings of deep neural networks, including tensors, extended operators, gradient descent algorithms, artificial neurons, dense networks, convolutional networks, residual networks, and automatic differentiation. - Conversational style, illustrations, and question-and-answer format make deep learning accessible and fun- Incremental approach constructs advanced concepts from first principles- Presents key ideas of machine learning using a small, manageable subset of the Scheme language- Suitable for anyone with knowledge of high school math and some programming experienceLibri GmbH, Europaallee 1, 36244 Bad Hersfeld Englisch. Su, Qingqing (illustrator).…

Taschenbuch. Zustand: Neu. The Little Learner | A Straight Line to Deep Learning | Daniel P. Friedman (u. a.) | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2023 | The MIT Press | EAN 9780262546379 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu. Su, Qingqing (illustrator). …

Taschenbuch. Zustand: Neu. Neuware -A highly accessible, step-by-step introduction to deep learning, written in an engaging, question-and-answer style.The Little Learner introduces deep learning from the bottom up, inviting students to learn by doing. With the characteristic humor and Socratic approach of classroom favorites The Little Schemer and The Little Typer, this kindred text explains the workings of deep neural networks by constructing them incrementally from first principles using little programs that build on one another. Starting from scratch, the reader is led through a complete implementation of a substantial application: a recognizer for noisy Morse code signals. Example-driven and highly accessible, The Little Learner covers all of the concepts necessary to develop an intuitive understanding of the workings of deep neural networks, including tensors, extended operators, gradient descent algorithms, artificial neurons, dense networks, convolutional networks, residual networks, and automatic differentiation. - Conversational style, illustrations, and question-and-answer format make deep learning accessible and fun- Incremental approach constructs advanced concepts from first principles- Presents key ideas of machine learning using a small, manageable subset of the Scheme language- Suitable for anyone with knowledge of high school math and some programming experience Englisch. Su, Qingqing (illustrator).…