000			01442nam a22002417a 4500
003			IIITD
005			20240514161011.0
008			240426b |||||||| |||| 00| 0 eng d
020			_a9789355424273
040			_aIIITD
082			_a005.133 _bHOW-D
100			_aHoward, Jeremy
245			_aDeep learning for coders with fastai and PyTorch : _bAI applications without a PhD _cby Jeremy Howard and Sylvain Gugger
260			_aBeijng : _bO'Reilly, _c©2023
300			_a594 p. : _bcol. ill. ; _c23 cm.
501			_aIncludes index.
505			_tPart 1. Deep Learning Journey. Your Deep Learning Journey From Model to Production Data Ethics _tPart 2. Understanding fastai's Applications. Under the Hood: Training a Digit Classifier Image Classification Other Computer Vision Problems Training a State-of-the-Art Model Collaborative Filtering Deep Dive Tabular Modeling Deep Dive NLP Deep Dive: RNNs Data Munging with fastai's Mid-Level API _tPart 3. Foundations of Deep Learning. A Language Model from Scratch Convolutional Neural Networks ResNets Application Architectures Deep Dive The Training Process _tPart 4. Deep Learning from Scratch. A Neural Net from the Foundations CNN Interpretation with CAM A fastai Learner from Scratch Concluding Thoughts.
650			_a Artificial Intelligence
650			_aComputer Science Books
700			_aGugger, Sylvain
700			_aChintala, Soumith _4Foreword
942			_2ddc _cBK _01
999			_c172519 _d172519