Data science in chemistry: artificial intelligence, big data, chemometrics and quantum computing with Jupyter
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| Main Author: | |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
Berlin ; Boston
De Gruyter
[2021]
|
| Series: | De Gruyter Graduate
|
| Subjects: | |
| Online Access: | http://www.degruyter.com/search?f_0=isbnissn&q_0=9783110629392&searchTitles=true Inhaltsverzeichnis |
| Physical Description: | XVIII, 522 Seiten Illustrationen, Diagramme (farbig) 24 cm x 17 cm |
| ISBN: | 9783110629392 3110629399 |
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MARC
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| 100 | 1 | |a Gressling, Thorsten |e Verfasser |0 (DE-588)1242738681 |4 aut | |
| 245 | 1 | 0 | |a Data science in chemistry |b artificial intelligence, big data, chemometrics and quantum computing with Jupyter |c Thorsten Gressling |
| 264 | 1 | |a Berlin ; Boston |b De Gruyter |c [2021] | |
| 264 | 4 | |c © 2021 | |
| 300 | |a XVIII, 522 Seiten |b Illustrationen, Diagramme (farbig) |c 24 cm x 17 cm | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 490 | 0 | |a De Gruyter Graduate | |
| 650 | 4 | |a Massendaten | |
| 650 | 4 | |a Künstliche Intelligenz | |
| 650 | 4 | |a Theoretische Chemie | |
| 650 | 0 | 7 | |a Data Science |0 (DE-588)1140936166 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Data Mining |0 (DE-588)4428654-5 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Computational chemistry |0 (DE-588)4290091-8 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Quantenchemie |0 (DE-588)4047979-1 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Chemie |0 (DE-588)4009816-3 |2 gnd |9 rswk-swf |
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| 653 | |a Künstliche Intelligenz | ||
| 653 | |a Theoretische Chemie | ||
| 653 | |a TB: Textbook | ||
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| 689 | 0 | 1 | |a Data Mining |0 (DE-588)4428654-5 |D s |
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| 689 | 1 | 0 | |a Chemometrie |0 (DE-588)4299578-4 |D s |
| 689 | 1 | 1 | |a Quantenchemie |0 (DE-588)4047979-1 |D s |
| 689 | 1 | 2 | |a Computational chemistry |0 (DE-588)4290091-8 |D s |
| 689 | 1 | |5 DE-604 | |
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| 999 | |a oai:aleph.bib-bvb.de:BVB01-032167167 | ||
Record in the Search Index
| _version_ | 1804181521104371713 |
|---|---|
| adam_text | CONTENTS
PREFACE
*
V
INTRODUCTION
*
XIII
TECHNICAL
SETUP
AND
NAMING
CONVENTIONS
*
XV
1
DATA
SCIENCE:
INTRODUCTION
*
1
2
DATA
SCIENCE:
THE
*
FOURTH
PARADIGM
*
OF
SCIENCE
*
4
3
RELATIONS
TO
OTHER
DOMAINS
AND
CHEMINFORMATICS
*
8
PART
A:
IT,
DATA
SCIENCE,
AND
AL
IT
BASICS
(CLOUD,
REST,
EDGE)
4
CHEMINFORMATICS
APPLICATION
LANDSCAPE
*
13
5
CLOUD,
FOG,
AND
AL
RUNTIME
ENVIRONMENTS
*
15
6
DEVOPS,
DATAOPS,
AND
MLOPS
*
19
7
HIGH-PERFORMANCE
COMPUTING
(HPC)
AND
CLUSTER
*
23
8
REST
AND
MQTT
-----
28
9
EDGE
DEVICES
AND
LOT
*
34
PROGRAMMING
10
PYTHON
AND
OTHER
PROGRAMMING
LANGUAGES
*
41
11
PYTHON
STANDARD
LIBRARIES
AND
CONDA
*
45
12
I
DE
*
S
AND
WORKFLOWS
*
55
13
JUPYTER
NOTEBOOKS
*
61
14
WORKING
WITH
NOTEBOOKS
AND
EXTENSIONS
*
68
15
NOTEBOOKS
AND
PYTHON
*
73
16
VERSIONING
CODE
AND
JUPYTER
NOTEBOOKS
*
80
17
INTEGRATION
OF
KNIME
AND
EXCEL
*
83
DATA
ENGINEERING
18
BIG
DATA
*
91
19
JUPYTER
AND
SPARK
*
96
20
FILES:
STRUCTURE
REPRESENTATIONS
*
102
21
FILES:
OTHER
FORMATS
*
106
VIII
*
CONTENTS
22
DATA
RETRIEVAL
AND
PROCESSING:
ETL
*
111
23
DATA
PIPELINES
*
114
24
DATA
INGESTION:
ONLINE
DATA
SOURCES
*
117
25
DESIGNING
DATABASES
*
125
26
DATA
SCIENCE
WORKFLOW
AND
CHEMICAL
DESCRIPTORS
*
130
DATA
SCIENCE
AS
FIELD
OF
ACTIVITY
27
COMMUNITY
AND
COMPETITIONS
*
139
28
DATA
SCIENCE
LIBRARIES
*
143
29
DEEP
LEARNING
LIBRARIES
*
145
30
ML
MODEL
SOURCES
AND
MARKETPLACES
*
148
31
MODEL
METRICS:
MLFLOW
AND
LUDWIG
*
152
INTRODUCTION
TO
ML
AND
AL
32
FIRST
GENERATION
(LOGIC
AND
SYMBOLS)
*
161
33
SECOND
GENERATION
(SHALLOW
MODELS)
*
164
34
SECOND
GENERATION:
REGRESSION
*
170
35
DECISION
TREES
*
179
36
SECOND
GENERATION:
CLASSIFICATION
*
182
37
SECOND
GENERATION:
CLUSTERING
AND
DIMENSIONALITY
REDUCTION
*
190
38
THIRD
GENERATION:
DEEP
LEARNING
MODELS
(ANN)
*
196
39
THIRD
GENERATION:
SNN
-
SPIKING
NEURAL
NETWORKS
*
204
40
XAL:
EXPLAINABLE
AL
*
206
PART
B:
JUPYTER
IN
CHEMINFORMATICS
PHYSICAL
CHEMISTRY
41
CRYSTALLOGRAPHIC
DATA
*
213
42
CRYSTALLOGRAPHIC
CALCULATIONS
*
215
43
CHEMICAL
KINETICS
AND
THERMOCHEMISTRY
*
219
44
REACTION
PATHS
AND
MIXTURES
*
223
45
THE
PERIODIC
TABLE
OF
ELEMENTS
*
227
46
APPLIED
THERMODYNAMICS
*
230
CONTENTS
*
IX
MATERIAL
SCIENCE
47
MATERIAL
INFORMATICS
*
235
48
MOLECULAR
DYNAM
ICS
WORKFLOWS
*
237
49
MOLECULAR
MECHANICS
*
241
50
VASP
-----
245
51
GAUSSIAN
(ASE)
*
249
52
GROMACS-----
251
53
AMBER,
NAMD,
AND
LAMMPS
-----255
54
FEATURIZE
MATERIALS
*
261
55
ASE
AND
NWCHEM
*
266
ORGANIC
CHEMISTRY
56
VISUALIZATION
*
273
57
MOLECULES
HANDLING
AND
NORMALIZATION
*
280
58
FEATURES
AND
2D
DESCRIPTORS
(OF
CARBON
COMPOUNDS)
*
287
59
WORKING
WITH
MOLECULES
AND
REACTIONS
*
294
60
FINGERPRINT
DESCRIPTORS
(ID)
*
299
61
SIMILARITIES
*
306
ENGINEERING,
LABORATORY,
AND
PRODUCTION
62
LABORATORY:
SILA
AND
ANIML
*
313
63
LABORATORY:
UMS
AND
DAILY
CALCULATIONS
*
319
64
LABORATORY:
ROBOTICS
AND
COGNITIVE
ASSISTANCE
*
325
65
CHEMICAL
ENGINEERING
*
330
66
REACTORS,
PROCESS
FLOW,
AND
SYSTEMS
ANALYSIS
*
334
67
PRODUCTION:
PLC
AND
OPC/UA
*
338
68
PRODUCTION:
PREDICTIVE
MAINTENANCE
*
342
PART
C:
DATA
SCIENCE
DATA
ENGINEERING
IN
ANALYTIC
CHEMISTRY
69
TITRATION
AND
CALORIMETRY
*
349
70
NMR
-----
352
X
*
CONTENTS
71
X-RAY-BASED
CHARACTERIZATION:
XAS,
XRD,
AND
EDX
*
354
72
MASS
SPECTROSCOPY
*
359
73
TGA,
DTG
-----
361
74
IR
AND
RAMAN
SPECTROSCOPY
*
364
75
AFM
AND
THERMOGRAM
ANALYSIS
*
368
76
GAS
CHROMATOGRAPHY-MASS
SPECTROMETRY
(GC-MS)
*
373
APPLIED
DATA
SCIENCE
AND
CHEMOMETRICS
77
SVD
CHEMOMETRICS
EXAMPLE
*
379
78
PRINCIPAL
COMPONENT
ANALYSIS
(PCA)
*
383
79
QSAR:
QUANTITATIVE
STRUCTURE-ACTIVITY
RELATIONSHIP
*
386
80
DEEPCHEM:
BINDING
AFFINITY
*
389
81
STOICHIOMETRY
AND
REACTION
BALANCING
*
393
APPLIED
ARTIFICIAL
INTELLIGENCE
82
ML
PYTHON
LIBRARIES
IN
CHEMISTRY
*
399
83
ALIN
DRUG
DESIGN
*
405
84
AUTOMATED
MACHINE
LEARNING
*
409
85
RETROSYNTHESIS
AND
REACTION
PREDICTION
*
412
86
CHEMML
-----
419
87
AL
IN
MATERIAL
DESIGN
*
423
KNOWLEDGE
AND
INFORMATION
88
ONTOLOGIES
AND
INFERENCING
*
429
89
ANALYZING
NETWORKS
*
436
90
KNOWLEDGE
INGESTION:
LABELING
AND
OPTICAL
RECOGNITION
*
443
91
CONTENT
MINING
AND
KNOWLEDGE
GRAPHS
*
450
PART
D:
QUANTUM
COMPUTING
AND
CHEMISTRY
INTRODUCTION
92
QUANTU
M
CONCEPTS
*
461
93
QCOMP:
TECHNOLOGY
VENDORS
*
471
94
QUANTUM
COMPUTING
SIMULATORS
*
477
95
QUANTUM
ALGORITHMS
*
480
96
QUANTUM
CHEMISTRY
SOFTWARE
(QCHEM)
*
485
CONTENTS
*
XI
QUANTUM
COMPUTING
APPLICATIONS
97
APPLICATION
EXAM
PIES
*
491
98
SIMULATING
MOLECULES
USING
VQE
*
495
99
STUDIES
ON
SMALL
CLUSTERS
OF
LIH,
BEH
2
,
AND
NAH
*
500
100
QUANTUM
MACHINE
LEARNING
(QAI)
*
504
CODE
INDEX
*
511
INDEX
*
519
|
| adam_txt |
CONTENTS
PREFACE
*
V
INTRODUCTION
*
XIII
TECHNICAL
SETUP
AND
NAMING
CONVENTIONS
*
XV
1
DATA
SCIENCE:
INTRODUCTION
*
1
2
DATA
SCIENCE:
THE
*
FOURTH
PARADIGM
*
OF
SCIENCE
*
4
3
RELATIONS
TO
OTHER
DOMAINS
AND
CHEMINFORMATICS
*
8
PART
A:
IT,
DATA
SCIENCE,
AND
AL
IT
BASICS
(CLOUD,
REST,
EDGE)
4
CHEMINFORMATICS
APPLICATION
LANDSCAPE
*
13
5
CLOUD,
FOG,
AND
AL
RUNTIME
ENVIRONMENTS
*
15
6
DEVOPS,
DATAOPS,
AND
MLOPS
*
19
7
HIGH-PERFORMANCE
COMPUTING
(HPC)
AND
CLUSTER
*
23
8
REST
AND
MQTT
-----
28
9
EDGE
DEVICES
AND
LOT
*
34
PROGRAMMING
10
PYTHON
AND
OTHER
PROGRAMMING
LANGUAGES
*
41
11
PYTHON
STANDARD
LIBRARIES
AND
CONDA
*
45
12
I
DE
*
S
AND
WORKFLOWS
*
55
13
JUPYTER
NOTEBOOKS
*
61
14
WORKING
WITH
NOTEBOOKS
AND
EXTENSIONS
*
68
15
NOTEBOOKS
AND
PYTHON
*
73
16
VERSIONING
CODE
AND
JUPYTER
NOTEBOOKS
*
80
17
INTEGRATION
OF
KNIME
AND
EXCEL
*
83
DATA
ENGINEERING
18
BIG
DATA
*
91
19
JUPYTER
AND
SPARK
*
96
20
FILES:
STRUCTURE
REPRESENTATIONS
*
102
21
FILES:
OTHER
FORMATS
*
106
VIII
*
CONTENTS
22
DATA
RETRIEVAL
AND
PROCESSING:
ETL
*
111
23
DATA
PIPELINES
*
114
24
DATA
INGESTION:
ONLINE
DATA
SOURCES
*
117
25
DESIGNING
DATABASES
*
125
26
DATA
SCIENCE
WORKFLOW
AND
CHEMICAL
DESCRIPTORS
*
130
DATA
SCIENCE
AS
FIELD
OF
ACTIVITY
27
COMMUNITY
AND
COMPETITIONS
*
139
28
DATA
SCIENCE
LIBRARIES
*
143
29
DEEP
LEARNING
LIBRARIES
*
145
30
ML
MODEL
SOURCES
AND
MARKETPLACES
*
148
31
MODEL
METRICS:
MLFLOW
AND
LUDWIG
*
152
INTRODUCTION
TO
ML
AND
AL
32
FIRST
GENERATION
(LOGIC
AND
SYMBOLS)
*
161
33
SECOND
GENERATION
(SHALLOW
MODELS)
*
164
34
SECOND
GENERATION:
REGRESSION
*
170
35
DECISION
TREES
*
179
36
SECOND
GENERATION:
CLASSIFICATION
*
182
37
SECOND
GENERATION:
CLUSTERING
AND
DIMENSIONALITY
REDUCTION
*
190
38
THIRD
GENERATION:
DEEP
LEARNING
MODELS
(ANN)
*
196
39
THIRD
GENERATION:
SNN
-
SPIKING
NEURAL
NETWORKS
*
204
40
XAL:
EXPLAINABLE
AL
*
206
PART
B:
JUPYTER
IN
CHEMINFORMATICS
PHYSICAL
CHEMISTRY
41
CRYSTALLOGRAPHIC
DATA
*
213
42
CRYSTALLOGRAPHIC
CALCULATIONS
*
215
43
CHEMICAL
KINETICS
AND
THERMOCHEMISTRY
*
219
44
REACTION
PATHS
AND
MIXTURES
*
223
45
THE
PERIODIC
TABLE
OF
ELEMENTS
*
227
46
APPLIED
THERMODYNAMICS
*
230
CONTENTS
*
IX
MATERIAL
SCIENCE
47
MATERIAL
INFORMATICS
*
235
48
MOLECULAR
DYNAM
ICS
WORKFLOWS
*
237
49
MOLECULAR
MECHANICS
*
241
50
VASP
-----
245
51
GAUSSIAN
(ASE)
*
249
52
GROMACS-----
251
53
AMBER,
NAMD,
AND
LAMMPS
-----255
54
FEATURIZE
MATERIALS
*
261
55
ASE
AND
NWCHEM
*
266
ORGANIC
CHEMISTRY
56
VISUALIZATION
*
273
57
MOLECULES
HANDLING
AND
NORMALIZATION
*
280
58
FEATURES
AND
2D
DESCRIPTORS
(OF
CARBON
COMPOUNDS)
*
287
59
WORKING
WITH
MOLECULES
AND
REACTIONS
*
294
60
FINGERPRINT
DESCRIPTORS
(ID)
*
299
61
SIMILARITIES
*
306
ENGINEERING,
LABORATORY,
AND
PRODUCTION
62
LABORATORY:
SILA
AND
ANIML
*
313
63
LABORATORY:
UMS
AND
DAILY
CALCULATIONS
*
319
64
LABORATORY:
ROBOTICS
AND
COGNITIVE
ASSISTANCE
*
325
65
CHEMICAL
ENGINEERING
*
330
66
REACTORS,
PROCESS
FLOW,
AND
SYSTEMS
ANALYSIS
*
334
67
PRODUCTION:
PLC
AND
OPC/UA
*
338
68
PRODUCTION:
PREDICTIVE
MAINTENANCE
*
342
PART
C:
DATA
SCIENCE
DATA
ENGINEERING
IN
ANALYTIC
CHEMISTRY
69
TITRATION
AND
CALORIMETRY
*
349
70
NMR
-----
352
X
*
CONTENTS
71
X-RAY-BASED
CHARACTERIZATION:
XAS,
XRD,
AND
EDX
*
354
72
MASS
SPECTROSCOPY
*
359
73
TGA,
DTG
-----
361
74
IR
AND
RAMAN
SPECTROSCOPY
*
364
75
AFM
AND
THERMOGRAM
ANALYSIS
*
368
76
GAS
CHROMATOGRAPHY-MASS
SPECTROMETRY
(GC-MS)
*
373
APPLIED
DATA
SCIENCE
AND
CHEMOMETRICS
77
SVD
CHEMOMETRICS
EXAMPLE
*
379
78
PRINCIPAL
COMPONENT
ANALYSIS
(PCA)
*
383
79
QSAR:
QUANTITATIVE
STRUCTURE-ACTIVITY
RELATIONSHIP
*
386
80
DEEPCHEM:
BINDING
AFFINITY
*
389
81
STOICHIOMETRY
AND
REACTION
BALANCING
*
393
APPLIED
ARTIFICIAL
INTELLIGENCE
82
ML
PYTHON
LIBRARIES
IN
CHEMISTRY
*
399
83
ALIN
DRUG
DESIGN
*
405
84
AUTOMATED
MACHINE
LEARNING
*
409
85
RETROSYNTHESIS
AND
REACTION
PREDICTION
*
412
86
CHEMML
-----
419
87
AL
IN
MATERIAL
DESIGN
*
423
KNOWLEDGE
AND
INFORMATION
88
ONTOLOGIES
AND
INFERENCING
*
429
89
ANALYZING
NETWORKS
*
436
90
KNOWLEDGE
INGESTION:
LABELING
AND
OPTICAL
RECOGNITION
*
443
91
CONTENT
MINING
AND
KNOWLEDGE
GRAPHS
*
450
PART
D:
QUANTUM
COMPUTING
AND
CHEMISTRY
INTRODUCTION
92
QUANTU
M
CONCEPTS
*
461
93
QCOMP:
TECHNOLOGY
VENDORS
*
471
94
QUANTUM
COMPUTING
SIMULATORS
*
477
95
QUANTUM
ALGORITHMS
*
480
96
QUANTUM
CHEMISTRY
SOFTWARE
(QCHEM)
*
485
CONTENTS
*
XI
QUANTUM
COMPUTING
APPLICATIONS
97
APPLICATION
EXAM
PIES
*
491
98
SIMULATING
MOLECULES
USING
VQE
*
495
99
STUDIES
ON
SMALL
CLUSTERS
OF
LIH,
BEH
2
,
AND
NAH
*
500
100
QUANTUM
MACHINE
LEARNING
(QAI)
*
504
CODE
INDEX
*
511
INDEX
*
519 |
| any_adam_object | 1 |
| any_adam_object_boolean | 1 |
| author | Gressling, Thorsten |
| author_GND | (DE-588)1242738681 |
| author_facet | Gressling, Thorsten |
| author_role | aut |
| author_sort | Gressling, Thorsten |
| author_variant | t g tg |
| building | Verbundindex |
| bvnumber | BV046757551 |
| classification_rvk | VC 6081 VC 6050 VC 6080 |
| classification_tum | CHE 020 |
| ctrlnum | (OCoLC)1224482549 (DE-599)DNB1207484733 |
| discipline | Chemie / Pharmazie Chemie |
| discipline_str_mv | Chemie / Pharmazie Chemie |
| format | Book |
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| id | DE-604.BV046757551 |
| illustrated | Illustrated |
| index_date | 2024-07-03T14:43:34Z |
| indexdate | 2024-07-10T08:52:58Z |
| institution | BVB |
| institution_GND | (DE-588)10095502-2 |
| isbn | 9783110629392 3110629399 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-032167167 |
| oclc_num | 1224482549 |
| open_access_boolean | |
| owner | DE-11 DE-29T DE-91G DE-BY-TUM DE-19 DE-BY-UBM DE-634 DE-20 DE-M347 |
| owner_facet | DE-11 DE-29T DE-91G DE-BY-TUM DE-19 DE-BY-UBM DE-634 DE-20 DE-M347 |
| physical | XVIII, 522 Seiten Illustrationen, Diagramme (farbig) 24 cm x 17 cm |
| publishDate | 2021 |
| publishDateSearch | 2021 |
| publishDateSort | 2021 |
| publisher | De Gruyter |
| record_format | marc |
| series2 | De Gruyter Graduate |
| spelling | Gressling, Thorsten Verfasser (DE-588)1242738681 aut Data science in chemistry artificial intelligence, big data, chemometrics and quantum computing with Jupyter Thorsten Gressling Berlin ; Boston De Gruyter [2021] © 2021 XVIII, 522 Seiten Illustrationen, Diagramme (farbig) 24 cm x 17 cm txt rdacontent n rdamedia nc rdacarrier De Gruyter Graduate Massendaten Künstliche Intelligenz Theoretische Chemie Data Science (DE-588)1140936166 gnd rswk-swf Data Mining (DE-588)4428654-5 gnd rswk-swf Computational chemistry (DE-588)4290091-8 gnd rswk-swf Quantenchemie (DE-588)4047979-1 gnd rswk-swf Chemie (DE-588)4009816-3 gnd rswk-swf Chemometrie (DE-588)4299578-4 gnd rswk-swf TB: Textbook Chemie (DE-588)4009816-3 s Data Mining (DE-588)4428654-5 s DE-604 Chemometrie (DE-588)4299578-4 s Quantenchemie (DE-588)4047979-1 s Computational chemistry (DE-588)4290091-8 s Data Science (DE-588)1140936166 s Walter de Gruyter GmbH & Co. KG (DE-588)10095502-2 pbl Erscheint auch als Online-Ausgabe, PDF 978-3-11-062945-3 Erscheint auch als Online-Ausgabe, EPUB 978-3-11-063053-4 X:MVB http://www.degruyter.com/search?f_0=isbnissn&q_0=9783110629392&searchTitles=true DNB Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=032167167&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Gressling, Thorsten Data science in chemistry artificial intelligence, big data, chemometrics and quantum computing with Jupyter Massendaten Künstliche Intelligenz Theoretische Chemie Data Science (DE-588)1140936166 gnd Data Mining (DE-588)4428654-5 gnd Computational chemistry (DE-588)4290091-8 gnd Quantenchemie (DE-588)4047979-1 gnd Chemie (DE-588)4009816-3 gnd Chemometrie (DE-588)4299578-4 gnd |
| subject_GND | (DE-588)1140936166 (DE-588)4428654-5 (DE-588)4290091-8 (DE-588)4047979-1 (DE-588)4009816-3 (DE-588)4299578-4 |
| title | Data science in chemistry artificial intelligence, big data, chemometrics and quantum computing with Jupyter |
| title_auth | Data science in chemistry artificial intelligence, big data, chemometrics and quantum computing with Jupyter |
| title_exact_search | Data science in chemistry artificial intelligence, big data, chemometrics and quantum computing with Jupyter |
| title_exact_search_txtP | Data science in chemistry artificial intelligence, big data, chemometrics and quantum computing with Jupyter |
| title_full | Data science in chemistry artificial intelligence, big data, chemometrics and quantum computing with Jupyter Thorsten Gressling |
| title_fullStr | Data science in chemistry artificial intelligence, big data, chemometrics and quantum computing with Jupyter Thorsten Gressling |
| title_full_unstemmed | Data science in chemistry artificial intelligence, big data, chemometrics and quantum computing with Jupyter Thorsten Gressling |
| title_short | Data science in chemistry |
| title_sort | data science in chemistry artificial intelligence big data chemometrics and quantum computing with jupyter |
| title_sub | artificial intelligence, big data, chemometrics and quantum computing with Jupyter |
| topic | Massendaten Künstliche Intelligenz Theoretische Chemie Data Science (DE-588)1140936166 gnd Data Mining (DE-588)4428654-5 gnd Computational chemistry (DE-588)4290091-8 gnd Quantenchemie (DE-588)4047979-1 gnd Chemie (DE-588)4009816-3 gnd Chemometrie (DE-588)4299578-4 gnd |
| topic_facet | Massendaten Künstliche Intelligenz Theoretische Chemie Data Science Data Mining Computational chemistry Quantenchemie Chemie Chemometrie |
| url | http://www.degruyter.com/search?f_0=isbnissn&q_0=9783110629392&searchTitles=true http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=032167167&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT gresslingthorsten datascienceinchemistryartificialintelligencebigdatachemometricsandquantumcomputingwithjupyter AT walterdegruytergmbhcokg datascienceinchemistryartificialintelligencebigdatachemometricsandquantumcomputingwithjupyter |