02031nam a22003135i 450000100090000000300050000900500170001400800410003101000170007202000310008902000260012002000310014603800100017704000230018704200080021008200160021810000280023424501670026225000190042926000370044826300090048530000090049433600260050333700280052933800270055752010470058465000290163185600570166021994071NUST20240829120604.0210414s2021    mau           000 0 eng    a  2021937264  a9780137470358q(paperback)  z9780137470297q(epub)  z9780137470259q(adobe pdf)  aAZHAR  aDLCbengerdacDLC  apcc  a006.31bEKM1 aEkman, Magnus,eauthor.10aLearning deep learning :btheory and practice of neural networks, computer vision, natural language processing, and transformers using tensorflow /cMagnus Ekman.  aFirst edition.  aBoston :bAddison-Wesley;c2022.  a2108  a688p  atextbtxt2rdacontent  aunmediatedbn2rdamedia  avolumebnc2rdacarrier  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"--cProvided by publisher.  aE-BOOKBANK.SEECSTEXTBOOK  uhttp://10.250.8.41:8080/xmlui/handle/123456789/41688