國立虎尾科技大學 |

Deep learning with applications using Python = chatbots and face, object, and speech recognition with TensorFlow and Keras /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Deep learning with applications using Python/ by Navin Kumar Manaswi.
其他題名:	chatbots and face, object, and speech recognition with TensorFlow and Keras /
作者:	Manaswi, Navin Kumar.
出版者:	Berkeley, CA :Apress : : 2018.,
面頁冊數:	xiii, 219 p. :ill., digital ; : 24 cm.;
Contained By:	Springer eBooks
標題:	Python (Computer program language) -
電子資源:	http://dx.doi.org/10.1007/978-1-4842-3516-4
ISBN:	9781484235164

Deep learning with applications using Python = chatbots and face, object, and speech recognition with TensorFlow and Keras /
Manaswi, Navin Kumar.

Deep learning with applications using Pythonchatbots and face, object, and speech recognition with TensorFlow and Keras /[electronic resource] :by Navin Kumar Manaswi. - Berkeley, CA :Apress :2018. - xiii, 219 p. :ill., digital ;24 cm.

1. Basics of Tensorflow -- 2. Basics of Keras -- 3. Multilayered Perceptron -- 4. Regression to MLP in Tensorflow -- 5. Regression to MLP in Keras -- 6. CNN in Visuals -- 7. CNN with Tensorflow -- 8. CNN with Keras -- 9. RNN and LSTM -- 10. Speech to Text and Vice Versa -- 11. Developing Chatbots -- 12. Face Detection and Face Recognition.

Build deep learning applications, such as computer vision, speech recognition, and chatbots, using frameworks such as TensorFlow and Keras. This book helps you to ramp up your practical know-how in a short period of time and focuses you on the domain, models, and algorithms required for deep learning applications. Deep Learning with Applications Using Python covers topics such as chatbots, natural language processing, and face and object recognition. The goal is to equip you with the concepts, techniques, and algorithm implementations needed to create programs capable of performing deep learning. This book covers intermediate and advanced levels of deep learning, including convolutional neural networks, recurrent neural networks, and multilayer perceptrons. It also discusses popular APIs such as IBM Watson, Microsoft Azure, and scikit-learn. You will: Work with various deep learning frameworks such as TensorFlow, Keras, and scikit-learn. Build face recognition and face detection capabilities Create speech-to-text and text-to-speech functionality Make chatbots using deep learning.

ISBN: 9781484235164

Standard No.: 10.1007/978-1-4842-3516-4doiSubjects--Topical Terms:

566246
Python (Computer program language)

LC Class. No.: QA76.73.P98

Dewey Class. No.: 005.133

Deep learning with applications using Python = chatbots and face, object, and speech recognition with TensorFlow and Keras /
LDR:02506nam a2200325 a 4500 001 925410
003 DE-He213
005 20180404141729.0
006 m d
007 cr nn 008maaau
008 190625s2018 cau s 0 eng d
020 $a 9781484235164 $q (electronic bk.)
020 $a 9781484235157 $q (paper)
024 7 $a 10.1007/978-1-4842-3516-4 $2 doi
035 $a 978-1-4842-3516-4
040 $a GP $c GP
041 0 $a eng
050 4 $a QA76.73.P98
072 7 $a UMA $2 bicssc
072 7 $a COM014000 $2 bisacsh
072 7 $a COM018000 $2 bisacsh
082 0 4 $a 005.133 $2 23
090 $a QA76.73.P98 $b M267 2018
100 1 $a Manaswi, Navin Kumar. $3 1203110
245 1 0 $a Deep learning with applications using Python $h [electronic resource] : $b chatbots and face, object, and speech recognition with TensorFlow and Keras / $c by Navin Kumar Manaswi.
260 $a Berkeley, CA : $b Apress : $b Imprint: Apress, $c 2018.
300 $a xiii, 219 p. : $b ill., digital ; $c 24 cm.
505 0 $a 1. Basics of Tensorflow -- 2. Basics of Keras -- 3. Multilayered Perceptron -- 4. Regression to MLP in Tensorflow -- 5. Regression to MLP in Keras -- 6. CNN in Visuals -- 7. CNN with Tensorflow -- 8. CNN with Keras -- 9. RNN and LSTM -- 10. Speech to Text and Vice Versa -- 11. Developing Chatbots -- 12. Face Detection and Face Recognition.
520 $a Build deep learning applications, such as computer vision, speech recognition, and chatbots, using frameworks such as TensorFlow and Keras. This book helps you to ramp up your practical know-how in a short period of time and focuses you on the domain, models, and algorithms required for deep learning applications. Deep Learning with Applications Using Python covers topics such as chatbots, natural language processing, and face and object recognition. The goal is to equip you with the concepts, techniques, and algorithm implementations needed to create programs capable of performing deep learning. This book covers intermediate and advanced levels of deep learning, including convolutional neural networks, recurrent neural networks, and multilayer perceptrons. It also discusses popular APIs such as IBM Watson, Microsoft Azure, and scikit-learn. You will: Work with various deep learning frameworks such as TensorFlow, Keras, and scikit-learn. Build face recognition and face detection capabilities Create speech-to-text and text-to-speech functionality Make chatbots using deep learning.
650 0 $a Python (Computer program language) $3 566246
650 0 $a Machine learning. $3 561253
650 1 4 $a Computer Science. $3 593922
650 2 4 $a Computing Methodologies. $3 640210
650 2 4 $a Python. $3 1115944
650 2 4 $a Big Data. $3 1017136
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer eBooks
856 4 0 $u http://dx.doi.org/10.1007/978-1-4842-3516-4
950 $a Professional and Applied Computing (Springer-12059)