Language:
English
繁體中文
Help
圖資館首頁
Login
Back
Switch To:
Labeled
|
MARC Mode
|
ISBD
Deep learning with applications usin...
~
Manaswi, Navin Kumar.
Deep learning with applications using Pythonchatbots and face, object, and speech recognition with TensorFlow and Keras /
Record Type:
Electronic resources : Monograph/item
Title/Author:
Deep learning with applications using Pythonby Navin Kumar Manaswi.
Reminder of title:
chatbots and face, object, and speech recognition with TensorFlow and Keras /
Author:
Manaswi, Navin Kumar.
Published:
Berkeley, CA :Apress :2018.
Description:
xiii, 219 p. :ill., digital ;24 cm.
Contained By:
Springer eBooks
Subject:
Python (Computer program language)
Online resource:
http://dx.doi.org/10.1007/978-1-4842-3516-4
ISBN:
9781484235164$q(electronic bk.)
Deep learning with applications using Pythonchatbots and face, object, and speech recognition with TensorFlow and Keras /
Manaswi, Navin Kumar.
Deep learning with applications using Python
chatbots and face, object, and speech recognition with TensorFlow and Keras /[electronic resource] :by Navin Kumar Manaswi. - Berkeley, CA :Apress :2018. - xiii, 219 p. :ill., digital ;24 cm.
1. Basics of Tensorflow -- 2. Basics of Keras -- 3. Multilayered Perceptron -- 4. Regression to MLP in Tensorflow -- 5. Regression to MLP in Keras -- 6. CNN in Visuals -- 7. CNN with Tensorflow -- 8. CNN with Keras -- 9. RNN and LSTM -- 10. Speech to Text and Vice Versa -- 11. Developing Chatbots -- 12. Face Detection and Face Recognition.
Build deep learning applications, such as computer vision, speech recognition, and chatbots, using frameworks such as TensorFlow and Keras. This book helps you to ramp up your practical know-how in a short period of time and focuses you on the domain, models, and algorithms required for deep learning applications. Deep Learning with Applications Using Python covers topics such as chatbots, natural language processing, and face and object recognition. The goal is to equip you with the concepts, techniques, and algorithm implementations needed to create programs capable of performing deep learning. This book covers intermediate and advanced levels of deep learning, including convolutional neural networks, recurrent neural networks, and multilayer perceptrons. It also discusses popular APIs such as IBM Watson, Microsoft Azure, and scikit-learn. You will: Work with various deep learning frameworks such as TensorFlow, Keras, and scikit-learn. Build face recognition and face detection capabilities Create speech-to-text and text-to-speech functionality Make chatbots using deep learning.
ISBN: 9781484235164$q(electronic bk.)
Standard No.: 10.1007/978-1-4842-3516-4doiSubjects--Topical Terms:
215247
Python (Computer program language)
LC Class. No.: QA76.73.P98
Dewey Class. No.: 005.133
Deep learning with applications using Pythonchatbots and face, object, and speech recognition with TensorFlow and Keras /
LDR
:02506nmm a2200325 a 4500
001
534169
003
DE-He213
005
20180404141729.0
006
m d
007
cr nn 008maaau
008
181205s2018 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
810290
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
215247
650
0
$a
Machine learning.
$3
188639
650
1 4
$a
Computer Science.
$3
212513
650
2 4
$a
Computing Methodologies.
$3
274528
650
2 4
$a
Python.
$3
763308
650
2 4
$a
Big Data.
$3
760530
710
2
$a
SpringerLink (Online service)
$3
273601
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)
based on 0 review(s)
ALL
電子館藏
Items
1 records • Pages 1 •
1
Inventory Number
Location Name
Item Class
Material type
Call number
Usage Class
Loan Status
No. of reservations
Opac note
Attachments
000000154759
電子館藏
1圖書
電子書
EB QA76.73.P98 M267 2018 2018
一般使用(Normal)
On shelf
0
1 records • Pages 1 •
1
Multimedia
Multimedia file
http://dx.doi.org/10.1007/978-1-4842-3516-4
Reviews
Add a review
and share your thoughts with other readers
Export
pickup library
Processing
...
Change password
Login