MLHub Desktop Survival Guide
Graham Williams
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Preface
Artificial Intelligence
About this Book
Technology
Terminology
Acknowledgements
Freedom, Utility, and Copyright
I Getting Started
1
Quick Start
2
The Machine Learning Hub
2.1
Install MLHub on Ubuntu
2.2
Setup MLHub on Ubuntu
2.3
Hello World
2.4
ml available
2.5
ml install
2.6
ml configure
2.7
ml readme
2.8
ml demo 🚧
2.9
ml gui 🚧
2.10
ml commands
2.11
ml command line options
2.12
ml rename
2.13
ml uninstall
2.14
Tips: Commands Auto Completion
2.15
Tips: Package Stops Working
2.16
Tips: Software Dependencies
2.17
MLHub on MacOS
3
MLHub Flutter App 🚣
3.1
MLHub Flutter Home Screen
3.2
MLHub Flutter Language Features
4
Pipelines
4.1
Pipeline: Adding Bounding Boxes to a Photo
4.2
Pipeline: Speech to Text with Translation to French to Speech
II Data Visualisation
5
Animations
5.1
animate configure
5.2
animate demo
5.3
animate build 🚣
6
Australian Shipping Ports 🚧
6.1
ports demo
III Cluster Analysis
7
K-Means Cluster Analysis
7.1
kmeans configure
7.2
kmeans quick start
7.3
kmeans demo
7.4
kmeans demo movie
7.5
kmeans demo iris
7.6
kmeans train
7.7
kmeans train movies
7.8
kmeans predict
7.9
kmeans normalise
7.10
kmeans visualise
7.11
kmeans visualise single variable
7.12
kmeans visualise two variables
7.13
kmeans example wine dataset
7.14
kmeans example wine dataset cluster
7.15
kmeans example wine normalised cluster
7.16
kmeans example wine clusters
7.17
kmeans pipelines
IV Association Analysis
8
Apriori Association Rules
8.1
apriori configure 🚧
8.2
apriori quick start
8.3
apriori demo 🚧
8.4
apriori itemsets
8.5
apriori train 🚧
8.6
apriori visualise 🚧
V Prediction and Classification
9
iris Plant Species Prediction 🚧
10
Rain Prediction
10.1
rain demo
10.2
rain demo data
10.3
rain demo fit the model
10.4
rain demo decision tree
10.5
rain demo visual decision tree
10.6
rain demo variable importance
10.7
rain demo visual variable importance
10.8
rain demo variable selection
10.9
rain demo predicting rain tomorrow
10.10
rain demo confusion matrix
10.11
rain demo risk chart
10.12
rain predict
11
Stella Graph Node Classification
11.1
sgnc demo
VI Computer Vision
12
Azure Computer Vision
12.1
azcv configure
12.2
azcv quick start
12.3
azcv demo
12.4
azcv gui
12.5
azcv adult
12.6
azcv category
12.7
azcv celebrities
12.8
azcv describe
12.9
azcv faces
12.10
azcv landmarks
12.11
azcv landmarks more
12.12
azcv landmarks pipeline
12.13
azcv objects
12.14
azcv ocr
12.15
azcv ocr handwritting
12.16
azcv ocr programming code
12.17
azcv ocr street signs
12.18
azcv tags
12.19
azcv thumbnail
12.20
azcv brands
12.21
azcv color
12.22
azcv type
13
Azure Facial Recognition
13.1
azface api key and endpoint
13.2
azface demo
13.3
azface detect
13.4
azface detect many faces
13.5
azface similar
13.6
TODO azface Pipelines
13.7
azface detect hats pipeline
14
Cars Identification
14.1
cars overview
14.2
cars identify
14.3
cars train 🚧
15
Colorize Photos 🚧
15.1
colorize configure
15.2
colorize quick start
15.3
colorize demo
15.4
colorize command
15.5
colorize resources
16
Face Detect 🚧
17
Object Identification 💔
18
OpenCV
18.1
opencv overview
18.2
opencv quick start
18.3
opencv blurry
18.4
opencv blurry pipeline
19
Plant Disease Prediction
19.1
plantdis configure
19.2
plantdis quick start 🚧
19.3
plantdis demo 🚧
19.4
plantdis diagnose 🚧
19.5
plantdis pipeline annotate image 🚧
20
U2Net Image Manipulation
20.1
u2net configure
20.2
u2net quick start 🚧
20.3
u2net demo
20.4
u2net demo continued
20.5
u2net cutout 🚧
20.6
u2net cutout video 🚧
20.7
u2net cutout with jpg output
20.8
u2net cutout alpha matting 🚧
20.9
u2net portrait 🚧
VII Natural Language Processing
21
Introduction
22
Azure Speech
22.1
azspeech configure
22.2
azspeech quick start
22.3
azspeech demo
22.4
azspeech recognise
22.5
azspeech synthesize
22.6
azspeech transcribe
22.7
azspeech transcribe languages
22.8
azspeech transcribe pipelines
22.9
azspeech transcribe video
22.10
azspeech translate
22.11
azspeech resources
23
Azure Text Analysis
23.1
aztext overview
23.2
aztext quick start 🚧
23.3
aztext demo
23.4
aztext supported
23.5
aztext analyze
23.6
aztext entities 🚧
23.7
aztext phrases 🚧
23.8
aztext language 🚧
23.9
aztext sentiment 🚧
23.10
aztext links 🚧
24
Azure Translate
24.1
aztranslate configure
24.2
aztranslate quick start
24.3
aztranslate demo
24.4
aztranslate translate
24.5
aztranslate translate other scripts
24.6
aztranslate supported
24.7
aztranslate limits
25
Deep Speech from Mozilla
25.1
deepspeech overview
25.2
deepspeech quick start
25.3
deepspeech demo
25.4
deepspeech transcribe
26
Hugging Face Model Repository 🚧
26.1
hugging configure
26.2
hugging quick start
26.3
hugging demo
26.4
hugging sentiment
26.5
hugging summarize
27
OpenAI 🚧
27.1
openai configure
27.2
openai quick start
27.3
openai identify
27.4
openai supported
27.5
openai transcribe
27.6
openai transcribe output formats
27.7
openai translate
27.8
openai resources
28
Zeyu Gao Natural Language Processing
28.1
zynlp demo
28.2
zynlp sentiment
VIII Miscellaneous
29
Bing Maps
29.1
bing configure
29.2
bing quick start
29.3
bing demo
29.4
bing geocode
29.5
bing geocode examples
30
Google Maps
30.1
google configure
30.2
google quick start
30.3
google demo
30.4
google geocode
30.5
google geocode examples
31
RelM Differential Privacy
32
Webcam Manipulation 🚧
32.1
webcam configure
32.2
webcam quick start
32.3
webcam gui 🚧
32.4
webcam blur 🚧
32.5
webcam contour 🚧
32.6
webcam edge 🚧
32.7
webcam emboss 🚧
32.8
webcam logo 🚧
32.9
webcam show 🚧
32.10
webcam thru 🚧
IX Appendix
33
MLHub Configuration File
33.1
Configuration Template
33.2
Configuration Meta Data
33.3
Configuration Process
33.4
Dependencies on Software and Libraries
33.5
Dependencies on Package Git Repository
33.6
Dependencies on Other Git Repositories
33.7
Dependencies on URLs
33.8
Dependencies File Caching
33.9
Dependencies Further Configuration
33.10
Dependencies Git LFS
33.11
Commands
34
MLHub Python and R Packages
34.1
mlhub get_cmd_cwd
34.2
mlhub get_private
34.3
mlhub mlask
35
Future
References
Published with Bookdown
Data Science Desktop Survival Guide
GNU/Linux Desktop Survival Guide
MLHub Desktop Survival Guide
The Essentials of Data Science
Data Mining with Rattle and R
MLHub Desktop Survival Guide
32.10
webcam thru 🚧
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