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Amend Data Preparation guide #136

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merged 18 commits into from
Jan 23, 2021
Merged

Amend Data Preparation guide #136

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14e0550
Adding Visualization sub-topic to Data preparation guide. Changes to …
neomatrix369 Oct 12, 2020
a763b51
Data preparation: reorganise the topics and sub-topics including the ToC
neomatrix369 Nov 7, 2020
2e69050
Data preparation: moving topics out of Data Cleaning into Data Prepro…
neomatrix369 Nov 7, 2020
026b778
Reorganising topics and sub-topics under Data Preparation
neomatrix369 Nov 11, 2020
b5a85c1
Further amendments to various sub-topics in the Data Prep guide
neomatrix369 Nov 11, 2020
b18d2e3
Fixed broken link in Data collection
neomatrix369 Nov 11, 2020
fed7b6c
Adding a line about the visualisation guide
neomatrix369 Nov 11, 2020
819df7f
Data prepation guide: fixing the Data Preprocessing... topic link in …
neomatrix369 Dec 1, 2020
f2429db
Data prepation guide: fixing all centralising to centralizing
neomatrix369 Dec 1, 2020
0b4bc2a
Data prepation guide: replacing first-person with third-person (I -> …
neomatrix369 Dec 1, 2020
e911c30
Data prepation guide: removing to and correcting the sentence
neomatrix369 Dec 1, 2020
33b56fa
Data prepation guide: removing referenced to FE terminology
neomatrix369 Dec 1, 2020
70c75ca
Data prepation guide: added lines and improved formating and language
neomatrix369 Dec 1, 2020
7c16732
Data prepation guide: adding a note about presence of paid/premium pr…
neomatrix369 Dec 1, 2020
6c00e91
Data prepation guide: fixed the description to the Data Cleaning section
neomatrix369 Dec 1, 2020
d33dde9
Data prepation guide: adding the Types of data section (expanding Tex…
neomatrix369 Dec 1, 2020
918048d
Data prepation guide: correcting the definitions of Normalisation and…
neomatrix369 Dec 10, 2020
e409ba7
small fixes and formatting enhancement
clone95 Jan 23, 2021
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2 changes: 1 addition & 1 deletion content/purgatorio/collect-and-prepare-data/data-collection.md
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Expand Up @@ -170,7 +170,7 @@ Then there is also ethics you do not want to miss out on and [the section to fol

With rising concerns over _privacy_ and _bias_, you want to be sure that the data collected does respect the ethics and standards in this field as much as possible.

To help with that as the awareness about things are improving, there are a lot of resources available, one such place to start would be [here](https://github.com/neomatrix369/awesome-ai-ml-dl/blob/naster/README-details.md#ethics--altruistic-motives). One of the resources mentioned there is that of a python package called [Deon](https://pypi.org/project/deon/). Interestingly it has a _digital checklist_ you can consult and see if they apply to what you are about to do.
To help with that as the awareness about things are improving, there are a lot of resources available, one such place to start would be [here](https://github.com/neomatrix369/awesome-ai-ml-dl/blob/master/README-details.md#ethics--altruistic-motives). One of the resources mentioned there is that of a python package called [Deon](https://pypi.org/project/deon/). Interestingly it has a _digital checklist_ you can consult and see if they apply to what you are about to do.
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#### Interpretability / Explainability

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