語系:
繁體中文
English
說明(常見問題)
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
Practical MATLAB Deep Learning = A P...
~
Thomas, Stephanie.
Practical MATLAB Deep Learning = A Project-Based Approach /
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Practical MATLAB Deep Learning/ by Michael Paluszek, Stephanie Thomas.
其他題名:
A Project-Based Approach /
作者:
Paluszek, Michael.
其他作者:
Thomas, Stephanie.
面頁冊數:
XV, 252 p. 111 illus., 100 illus. in color.online resource. :
Contained By:
Springer Nature eBook
標題:
Programming Techniques. -
電子資源:
https://doi.org/10.1007/978-1-4842-5124-9
ISBN:
9781484251249
Practical MATLAB Deep Learning = A Project-Based Approach /
Paluszek, Michael.
Practical MATLAB Deep Learning
A Project-Based Approach /[electronic resource] :by Michael Paluszek, Stephanie Thomas. - 1st ed. 2020. - XV, 252 p. 111 illus., 100 illus. in color.online resource.
1 What is Deep Learning? -- 2 MATLAB Machine and Deep Learning Toolboxes -- 3 Finding Circles with Deep Learning -- 4 Classifying Movies -- 5 Algorithmic Deep Learning -- 6 Tokamak Disruption Detection -- 7 Classifying a Pirouette -- 8 Completing Sentences -- 9 Terrain Based Navigation -- 10 Stock Prediction -- 11 Image Classification -- 12 Orbit Determination.
Harness the power of MATLAB for deep-learning challenges. This book provides an introduction to deep learning and using MATLAB's deep-learning toolboxes. You’ll see how these toolboxes provide the complete set of functions needed to implement all aspects of deep learning. Along the way, you'll learn to model complex systems, including the stock market, natural language, and angles-only orbit determination. You’ll cover dynamics and control, and integrate deep-learning algorithms and approaches using MATLAB. You'll also apply deep learning to aircraft navigation using images. Finally, you'll carry out classification of ballet pirouettes using an inertial measurement unit to experiment with MATLAB's hardware capabilities. You will: Explore deep learning using MATLAB and compare it to algorithms Write a deep learning function in MATLAB and train it with examples Use MATLAB toolboxes related to deep learning Implement tokamak disruption prediction.
ISBN: 9781484251249
Standard No.: 10.1007/978-1-4842-5124-9doiSubjects--Topical Terms:
669781
Programming Techniques.
LC Class. No.: QA76.7-76.73
Dewey Class. No.: 005.13
Practical MATLAB Deep Learning = A Project-Based Approach /
LDR
:02718nam a22004095i 4500
001
1022468
003
DE-He213
005
20200702121852.0
007
cr nn 008mamaa
008
210318s2020 xxu| s |||| 0|eng d
020
$a
9781484251249
$9
978-1-4842-5124-9
024
7
$a
10.1007/978-1-4842-5124-9
$2
doi
035
$a
978-1-4842-5124-9
050
4
$a
QA76.7-76.73
050
4
$a
QA76.76.C65
072
7
$a
UMX
$2
bicssc
072
7
$a
COM051010
$2
bisacsh
072
7
$a
UMX
$2
thema
072
7
$a
UMC
$2
thema
082
0 4
$a
005.13
$2
23
100
1
$a
Paluszek, Michael.
$4
aut
$4
http://id.loc.gov/vocabulary/relators/aut
$3
1070180
245
1 0
$a
Practical MATLAB Deep Learning
$h
[electronic resource] :
$b
A Project-Based Approach /
$c
by Michael Paluszek, Stephanie Thomas.
250
$a
1st ed. 2020.
264
1
$a
Berkeley, CA :
$b
Apress :
$b
Imprint: Apress,
$c
2020.
300
$a
XV, 252 p. 111 illus., 100 illus. in color.
$b
online resource.
336
$a
text
$b
txt
$2
rdacontent
337
$a
computer
$b
c
$2
rdamedia
338
$a
online resource
$b
cr
$2
rdacarrier
347
$a
text file
$b
PDF
$2
rda
505
0
$a
1 What is Deep Learning? -- 2 MATLAB Machine and Deep Learning Toolboxes -- 3 Finding Circles with Deep Learning -- 4 Classifying Movies -- 5 Algorithmic Deep Learning -- 6 Tokamak Disruption Detection -- 7 Classifying a Pirouette -- 8 Completing Sentences -- 9 Terrain Based Navigation -- 10 Stock Prediction -- 11 Image Classification -- 12 Orbit Determination.
520
$a
Harness the power of MATLAB for deep-learning challenges. This book provides an introduction to deep learning and using MATLAB's deep-learning toolboxes. You’ll see how these toolboxes provide the complete set of functions needed to implement all aspects of deep learning. Along the way, you'll learn to model complex systems, including the stock market, natural language, and angles-only orbit determination. You’ll cover dynamics and control, and integrate deep-learning algorithms and approaches using MATLAB. You'll also apply deep learning to aircraft navigation using images. Finally, you'll carry out classification of ballet pirouettes using an inertial measurement unit to experiment with MATLAB's hardware capabilities. You will: Explore deep learning using MATLAB and compare it to algorithms Write a deep learning function in MATLAB and train it with examples Use MATLAB toolboxes related to deep learning Implement tokamak disruption prediction.
650
2 4
$a
Programming Techniques.
$3
669781
650
2 4
$a
Mathematics of Computing.
$3
669457
650
2 4
$a
Hardware and Maker.
$3
1114124
650
2 4
$a
Artificial Intelligence.
$3
646849
650
1 4
$a
Programming Languages, Compilers, Interpreters.
$3
669782
650
0
$a
Computer programming.
$3
527822
650
0
$a
Computer science—Mathematics.
$3
1253519
650
0
$a
Computer input-output equipment.
$3
559611
650
0
$a
Artificial intelligence.
$3
559380
650
0
$a
Programming languages (Electronic computers).
$3
1127615
700
1
$a
Thomas, Stephanie.
$4
aut
$4
http://id.loc.gov/vocabulary/relators/aut
$3
1070181
710
2
$a
SpringerLink (Online service)
$3
593884
773
0
$t
Springer Nature eBook
776
0 8
$i
Printed edition:
$z
9781484251232
776
0 8
$i
Printed edition:
$z
9781484251256
856
4 0
$u
https://doi.org/10.1007/978-1-4842-5124-9
912
$a
ZDB-2-CWD
912
$a
ZDB-2-SXPC
950
$a
Professional and Applied Computing (SpringerNature-12059)
950
$a
Professional and Applied Computing (R0) (SpringerNature-43716)
筆 0 讀者評論
多媒體
評論
新增評論
分享你的心得
Export
取書館別
處理中
...
變更密碼[密碼必須為2種組合(英文和數字)及長度為10碼以上]
登入