| 000 | 01821nam\a2200253\a\4500 | ||
|---|---|---|---|
| 001 | 57681 | ||
| 005 | 20260118115516.0 | ||
| 008 | 260118s2021 mau 000 0 eng | ||
| 020 |
_a9789356063976 _q(paperback) |
||
| 040 |
_aDLC _beng _erda _cDLC _dBD-DhIUB |
||
| 082 |
_222 _a006.31 _bE368l |
||
| 100 | 1 |
_aEkman, Magnus, _eauthor. |
|
| 245 | 1 | 0 |
_aLearning deep learning : _btheory and practice of neural networks, computer vision, nlp, and transformers using tensorflow / _cMagnus Ekman. |
| 250 | _aFirst edition. | ||
| 260 |
_aIndia: _bPearson India Education services Pvt. Ltd., _c2022 |
||
| 300 | _apages cm | ||
| 520 | _a"Deep learning is at the heart of many of today's most exciting advances in machine learning and artificial intelligence. Pioneering applications at companies like Tesla, Google, and Facebook are now being followed by massive investments in fields ranging from finance to healthcare. Now, there's a complete guide to deep learning with TensorFlow, the #1 Python library for building these breakthrough applications. Magnus Ekman illuminates both the underlying concepts and the hands-on programming techniques you'll need, even if you have no machine learning experience. Throughout, you'll find concise, well-annotated code examples using TensorFlow and the Keras API; for comparison and easy migration between frameworks, complementary examples in PyTorch are provided online. Ekman also explains enough of the mathematics to help newcomers grasp how deep learning actually works. The guide concludes by previewing emerging trends in deep learning, and exploring the challenging ethical issues surrounding its use"-- | ||
| 526 |
_aCSE _bps _lREF |
||
| 541 | _aRisaam | ||
| 650 | 0 |
_aDeep learning _97100 |
|
| 650 | 0 |
_aNeural networks _97078 |
|
| 942 |
_2ddc _cBK |
||
| 999 |
_c57681 _d57855 |
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