Benchmarking calling Oracle Machine Learning using REST

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Over the past year I’ve been presenting, blogging and sharing my experiences of using REST to expose Oracle Machine Learning models to developers in other languages, for example Python.

One of the questions I’ve been asked is, Does it scale?

Although I’ve used it in several projects to great success, there are no figures I can report publicly on how many REST API calls can be serviced ūüė¶

But this can be easily done, and the results below are based on using and Oracle Autonomous Data Warehouse (ADW) on the Oracle Always Free.

The machine learning model is built on a Wine reviews data set, using Oracle Machine Learning Notebook as my tool to write some SQL and PL/SQL to build out a model to predict Good or Bad wines, based on the Prices and other characteristics of the wine. A REST API was built using this model to allow for a developer to pass in wine descriptors and returns two values to indicate if it would be a Good or Bad wine and the probability of this prediction.

No data is stored in the database. I only use the machine learning model to make the prediction

I built out the REST API using APEX, and here is a screenshot of the GET API setup.

Here is an example of some Python code to call the machine learning model to make a prediction.

import json
import requests

country = 'Portugal'
province = 'Douro'
variety = 'Portuguese Red'
price = '30'

resp = requests.get('https://jggnlb6iptk8gum-adw2.adb.us-ashburn-1.oraclecloudapps.com/ords/oml_user/wine/wine_pred/'+country+'/'+province+'/'+'variety'+'/'+price)
json_data = resp.json()
print (json.dumps(json_data, indent=2))

—–

{
  "pred_wine": "LT_90_POINTS",
  "prob_wine": 0.6844716987704507
}

But does this scale, as in how many concurrent users and REST API calls can it handle at the same time.

To test this I multi-threaded processes in Python to call a Python function to call the API, while ensuring a range of values are used for the input parameters. Some additional information for my tests.

  • Each function call included two REST API calls
  • Test effect of creating X processes, at same time
  • Test effect of creating X processes in batches of Y agents
  • Then, the above, with function having one REST API call and also having two REST API calls, to compare timings
  • Test in range of parallel process from 10 to 1,000 (generating up to 2,000 REST API calls at a time)

Some of the results. The table shows the time(*) in seconds to complete the number of processes grouped into batches (agents). My laptop was the limiting factor in these tests. It wasn’t able to test when the number of parallel processes when above 500. That is why I broke them into batches consisting of X agents

* this is the total time to run all the Python code, including the time taken to create each process.

Some observations:

  • Time taken to complete each function/process was between 0.45 seconds and 1.65 seconds, for two API calls.
  • When only one API call, time to complete each function/process was between 0.32 seconds and 1.21 seconds
  • Average time for each function/process was 0.64 seconds for one API functions/processes, and 0.86 for two API calls in function/process
  • Table above illustrates the overhead associated with setting up, calling, and managing these processes

As you can see, even with the limitations of my laptop, using an Oracle Database, in-database machine learning and REST can be used to create a Micro-Service type machine learning scoring engine. Based on these numbers, this machine learning micro-service would be able to handle and process a large number of machine learning scoring in Real-Time, and these numbers would be well within the maximum number of such calls in most applications. I’m sure I could process more parallel processes if I deployed on a different machine to my laptop and maybe used a number of different machines at the same time

How many applications within you enterprise needs to process move than 6,000 real-time machine learning scoring per minute?  This shows us the Oracle Always Free offering is capable and suitable for most applications.

Now, if you are processing more than those numbers per minutes then perhaps you need to move onto the paid options.

What next? I’ll spin up two VMs on Oracle Always Free, install Python, copy code into these VMs and have then run in parallel ūüôā

 

Irish Whiskey Distilleries Data Set

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I’ve been building some Irish Whiskey data sets, and the first of these data sets contains details of all the Whiskey Distilleries in Ireland. This page contains the following:

  • Table describing the attributes/features of the data set
  • Data set, in a scroll able region
  • Download data set in different formats
  • Map of the Distilleries
  • Subscribe to Twitter List containing these Distilleries, and some Twitter Hash Tags
  • How to send me updates, corrections and details of Distilleries I’ve missed

If you use this data set (and my other data sets) make sure to add a reference back to data set webpage. Let me know if you use the data set is an interesting way, share the details with me and I’ll share it on my blog and social media for you.

This data set will have it’s own Irish Distilleries webpage and all updates to the data set and other information will be made there. Check out that webpage for the latest version of things.

Data Set Description

Data set contains 45 Distilleries.

ATTRIBUTE NAME DESCRIPTION
Distillery Name of the Distillery
County County / Area where distillery is located
Address Full address of the distillery
EIRCODE EirCode for distillery in Ireland. Distilleries in Northern Ireland will not have an EIRCODE
NI_Postcode Post code of distilleries located in Northern Ireland
Tours Does the distillery offer tours to visitors (Yes/No)
Web_Site Web site address
Twitter The twitter name of the distillery
Lat Latitude for the distillery
Long Longitude for the distillery
Notes_Parent_Company Contains other descriptive information about the distillery, founded by, parent company, etc.

Data Set (scroll able region)

Data set contains 45 Distilleries.

DISTILLERY COUNTY ADDRESS EIRCODE NI_POSTCODE TOURS WEB_SITE TWITTER LAT LONG NOTES_PARENT_COMPANY
Ballykeefe Distillery Kilkenny Kyle, Ballykeefe, Cuffsgrange, County Kilkenny,‚ÄĮR95 NR50, Ireland R95 NR50 Yes https://ballykeefedistillery.ie ¬†@BallykeefeD 52.602034 -7.375774 Ging Family
Belfast Distillery Antrim Crumlin Road Goal, Crumlin Road, Belfast, BT14 6ST, United Kingdom BT14 6ST No http://www.belfastdistillery.com  @BDCIreland 54.609718 -5.941994 J&J McConnell
Blacks Distillery Cork Farm Lane, Kinsale, Co. Cork P17 XW70 No https://www.blacksbrewery.com  @BlacksBrewery 51.710969 -8.515579
Blackwater Waterford Church Road, Ballinlevane East, Ballyduff, Co. Waterford, P51 C5C6 P51 C5C6 No https://blackwaterdistillery.ie/  @BlackDistillery 52.147581 -8.052973
Boann Louth Lagavooren, Platin Rd., Drogheda, Co. Louth, A92 X593 A92 X593 Yes http://boanndistillery.ie/  @Boanndistillery 53.69459 -6.366558 Cooney Family
Bow Street Dublin Bow St, Smithfield Village, Dublin 7 D07 N9VH Yes https://www.jamesonwhiskey.com/en-IE/visit-us/jameson-distillery-bow-st  @jamesonireland 53.348415 -6.277266 Pernod Ricard
Bushmills Distillery Antrim 2 Distillery Rd, Bushmills BT57 8XH, United Kingdom BT57 8XH Yes https://bushmills.com  @BushmillsGlobal 55.202936 -6.517221
Cape Clear Cork Cape Clear Island, Knockannamaurnagh, Skibbereen, Co. Cork P81 RX70 No https://www.capecleardistillery.com/  @capedistillery 51.4509 -9.483047
Clonakilty Cork The Waterfront, Clonakilty, Co. Cork P85 EW82 Yes https://www.clonakiltydistillery.ie/  @clondistillery 51.62165 -8.8855 Scully Family
Connacht Whiskey Distillery Mayo Belleek, Ballina, Co Mayo, F26 P932 F26 P932 Yes https://connachtwhiskey.com  @connachtwhiskey 54.122131 -9.143779
Cooley Distillery Louth Dundalk Rd, Maddox Garden, Carlingford, Dundalk, Co. Louth A91 FX98 Yes 53.996544 -6.221563 Beam Suntory
Copeland Distillery Down 43 Manor Street, Donaghadee, Co Down, Northern Ireland, BT21 0HG BT21 0HG Yes https://copelanddistillery.com @CopelandDistill 54.642699 -5.532739
Dingle Distillery Kerry Farranredmond, DIngle, Co. Kerry V92 E7YD Yes https://dingledistillery.ie/  @DingleWhiskey 52.141928 -10.289287
Dublin Liberties Dublin 33 Mill Street, Dublin 8, D08 V221 D08 V221 Yes https://thedld.com  @WeAreTheDLD 53.337343 -6.276367
Echlinville Distillery Down 62 Gransha Rd, Kircubbin, Newtownards BT22 1AJ, United Kingdom BT22 1AJ Yes https://echlinville.com/  @Echlinville 54.46909 -5.509397
Glendalough Wicklow Unit 9 Newtown Business And Enterprise Centre, Newtown Mount Kennedy, Co. Wicklow, A63 A439 A63 A439 No https://www.glendaloughdistillery.com/  @GlendaloughDist 53.085011 -6.1074016 Mark Anthony Brands International
Great Northern Distillery Louth Carrickmacross Road, Dundalk, Co. Louth, Ireland, A91 P8W9 A91 P8W9 No https://gndireland.com/  @GNDistillery 54.001574 -6.40964 Teeling Family, formally of Cooley Distillery
Hinch Distillery Down 19 Carryduff Road, Boardmills, Ballynahinch, Down, United Kingdom BT27 6TZ No https://hinchdistillery.com/  @hinchdistillery 54.461021 -5.903713
Kilbeggan Distillery Westmeath Lower Main St, Aghamore, Kilbeggan, Co. Westmeath, Ireland N91 W67N Yes https://www.kilbegganwhiskey.com  @Kilbeggan 53.369369 -7.502809 Beam Suntory
Kinahan’s Distillery Dublin 44 Fitzwilliam Place, Dublin D02 P027 No https://kinahanswhiskey.com @KinahansLL Sources Whiskey from around ireland
Lough Gill Sligo Hazelwood Avenue, Cams, Co. Sligo F91 Y820 F91 Y820 Yes https://www.athru.com/  @athruwhiskey 54.255318 -8.433156
Lough Mask Mayo Drioglann Loch Measc Teo, Killateeaun, Tourmakeady, Co. Mayo F12 PK75 Yes https://www.loughmaskdistillery.com/  @lough_mask 53.611819 -9.444077 David Raethorne
Lough Ree Longford Main Street, Lanesborough, Co. Longford N39 P229 No https://www.lrd.ie  @LoughReeDistill 53.673328 -7.99043
Matt D’Arcy Down 27 St Marys St, Newry BT34 2AA, United Kingdom BT34 2AA No http://www.mattdarcys.com ¬†@mattdarcys 54.172817 -6.339367
Midleton Distillery Cork Old Midleton Distillery, Distillery Walk, Midleton, Co. Cork.  P25 Y394 P25 Y394 Yes https://www.jamesonwhiskey.com/en-IE/visit-us/jameson-distillery-midleton  @jamesonireland 51.916344 -8.165174 Pernod Ricard
Nephin Mayo Nephin Whiskey Company, Nephin Square, Lahardane, Co. Mayo F26 W2H9 No http://nephinwhiskey.com/  @NephinWhiskey 54.029011 -9.32211
Pearse Lyons Distillery Dublin 121-122 James’s Street Dublin 8, D08 ET27 D08 ET27 Yes https://www.pearselyonsdistillery.com  @PLDistillery 53.343708 -6.289351
Powerscourt Wicklow Powerscourt Estate, Enniskerry, Co. Wicklow, A98 A9T7 A98 A9T7 Yes https://powerscourtdistillery.com/  @PowerscourtDist 53.184167 -6.190794
Rademon Estate Distillery Down Rademon Estate Distillery, Downpatrick, County Down, United Kingdom BT30 9HR Yes https://rademonestatedistillery.com  @RademonEstate 54.396039 -5.790968
Roe & Co Dublin 92 James’s Street, Dublin 8 D08 YYW9 Yes https://www.roeandcowhiskey.com 53.343731 -6.285673
Royal Oak Distillery Carlow Clorusk Lower, Royaloak, Co. Carlow R21 KR23 Yes https://royaloakdistillery.com/  @royaloakwhiskey 52.703341 -6.978711 Saronno
Scotts Irish Distillery Fermanagh Main Street, Garrison, Co Fermanagh, BT93 4ER, United Kingdom BT93 4ER No http://scottsirish.com 54.417726 -8.083534
Skellig Six 18 Distillery Kerry Valentia Rd, Garranearagh, Cahersiveen, Co. Kerry, V23 YD89 V23 YD89 Yes https://skelligsix18distillery.ie  @SkelligSix18 51.935701 -10.239549
Slane Castle Distillery Meath Slane Castle, Slane, Co. Meath C15 F224 Yes https://www.slaneirishwhiskey.com/  @slanewhiskey 53.711065 -6.562735 Brown-Forman & Conyngham Family
Sliabh Liag Donegal Line Road, Carrick, Co Donegal, F94 X9DX F94 X9DX Yes https://www.sliabhliagdistillers.com/  @sliabhliagdistl 54.6545 -8.633847
Teeling Whiskey Distillery Dublin 13-17 Newmarket, The Liberties, Dublin 8, D08 KD91 D08 KD91 Yes https://teelingwhiskey.com/  @TeelingWhiskey 53.337862 -6.277123 Teeling Family
The Quiet Man Derry 10 Rossdowney Rd, Londonderry BT47 6NS, United Kingdom BT47 6NS No http://www.thequietmanirishwhiskey.com/  @quietmanwhiskey 54.995344 -7.301312 Niche Drinks
The Shed Distillery Leitrim Carrick on shannon Road, Drumshanbo, Co. Leitrim N41 R6D7 No http://thesheddistillery.com/  @SHEDDISTILLERY 54.047145 -8.04358
Thomond Gate Distillery Limerick No https://thomondgatewhiskey.com/ @ThomondW Nicholas Ryan
Tipperary Tipperary Newtownadam, Cahir, Co. Tipperary No http://tipperarydistillery.ie/  @TippDistillery 52.358622 -7.881875
Tullamore Distillery Offaly Bury Quay, Tullamore, Co. Offaly R35 XW13 Yes https://www.tullamoredew.com  @TullamoreDEW 53.377774 -7.492944
Walsh Whiskey Distillery Carlow Equity House, Deerpark Business Park, Dublin Rd, Carlow R93 K7W4 No http://walshwhiskey.com/  @walshwhiskey 52.853417 -6.883916 Walsh Family
Waterford Distillery Waterford 9 Mary Street, Grattan Quay, Waterford City, Co. Waterford X91 KF51 No https://waterfordwhisky.com/  @waterforddram 52.264308 -7.120997 Renegade Spirits Ireland Ltd
Wayward Irish Distillery Kerry Lakeview House & Estate, Fossa Road, Maulagh, Killarney, Co. Kerry, V93 F7Y5 V93 F7Y5 No https://www.waywardirish.com ¬†@wayward_irish 52.071045 -9.590709 O’Connell Fomily
West Cork Distillers Cork Marsh Rd, Marsh, Skibbereen, Co. Cork P81 YY31 No http://www.westcorkdistillers.com/  @WestCorkDistill 51.557804 -9.268941

Download Data Set

Irish_Whiskey_Distilleries – Excel Spreadsheet

Irish_Whiskey_Distilleries.csv – Zipped CSV file

I’ll be adding some additional formats soon.

Map of Distilleries

Here is a map with the Distilleries plotted using Google Maps.

Screenshot 2020-02-13 15.22.40

Twitter Lists & Twitter Hash Tags

I’ve created a Twitter list containing the twitter accounts for all of these distilleries. You can subscribe to the list to get all the latest posts from these distilleries

Irish Whishkey Distillery Twitter List

Have a look out for these twitter hash tags on a Friday, Saturday or Sunday night, as people from around the world share what whiskeys they are tasting that evening. Irish and Scotish Whiskies are the most common.

#FridayNightDram
#FridayNightSip
#SaturdayNightSip
#SaturdayNightDram
#SundayNightSip
#SundayNightDram

How to send me updates, corrections and details of Distilleries I’ve missed

Let me know, via the my Contact page,¬† if you see any errors in the data set, especially if I’m missing any distilleries.

Storing and processing Unicode characters in Oracle

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Unicode is a computing industry standard for the consistent encoding, representation, and handling of text expressed in most of the world’s writing systems (Wikipedia). The standard is maintained by the Unicode Consortium, and contains over 137,994 characters (137,766 graphic characters, 163 format characters and 65 control characters).

The NVARCHAR2 is Unicode data type that can store Unicode characters in an Oracle Database. The character set of the NVARCHAR2 is national character set specified at the database creation time. Use the following to determine the national character set for your database.

SELECT *
FROM nls_database_parameters
WHERE PARAMETER = 'NLS_NCHAR_CHARACTERSET';

For my database I’m using an Oracle Autonomous Database. This query returns the character set AL16UTF16. This character set encodes Unicode data in the UTF-16 encoding and uses 2 bytes to store a character.

When creating an attribute with this data type, the size value (max 4000) determines the number of characters allowed. The actual size of the attribute will be double.

Let’s setup some data to test this data type.

CREATE TABLE demo_nvarchar2 (
   attribute_name NVARCHAR2(100));

INSERT INTO demo_nvarchar2 
VALUES ('This is a test for nvarchar2');

The string is 28 characters long. We can use the DUMP function to see the details of what is actually stored.

SELECT attribute_name, DUMP(attribute_name,1016)
FROM demo_nvarchar2;

The DUMP function returns a VARCHAR2 value that contains the datatype code, the length in bytes, and the internal representation of a value.

 

You can see the difference in the storage size of the NVARCHAR2 and the VARCHAR2 attributes.

Valid values for the return_format are 8, 10, 16, 17, 1008, 1010, 1016 and 1017. These values are assigned the following meanings:


8 – octal notation
10 – decimal notation
16 – hexadecimal notation
17 – single characters
1008 – octal notation with the character set name
1010 – decimal notation with the character set name
1016 – hexadecimal notation with the character set name
1017 – single characters with the character set name

The returned value from the DUMP function gives the internal data type representation. The following table lists the various codes and their description.

Code Data Type
1 VARCHAR2(size [BYTE | CHAR])
1 NVARCHAR2(size)
2 NUMBER[(precision [, scale]])
8 LONG
12 DATE
21 BINARY_FLOAT
22 BINARY_DOUBLE
23 RAW(size)
24 LONG RAW
69 ROWID
96 CHAR [(size [BYTE | CHAR])]
96 NCHAR[(size)]
112 CLOB
112 NCLOB
113 BLOB
114 BFILE
180 TIMESTAMP [(fractional_seconds)]
181 TIMESTAMP [(fractional_seconds)] WITH TIME ZONE
182 INTERVAL YEAR [(year_precision)] TO MONTH
183 INTERVAL DAY [(day_precision)] TO SECOND[(fractional_seconds)]
208 UROWID [(size)]
231 TIMESTAMP [(fractional_seconds)] WITH LOCAL TIMEZONE

 

OCI Data Science ‚Äď Create a Project & Notebook, and Explore the Interface

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In my previous blog post I went through the steps of setting up OCI to allow you to access OCI Data Science. Those steps showed the setup and configuration for your Data Science Team.

Screenshot 2020-02-11 20.46.42

In this post I will walk through the steps necessary to create an OCI Data Science Project and Notebook, and will then Explore the basic Notebook environment.

1 – Create a Project

From the main menu on the Oracle Cloud home page select Data Science -> Projects from the menu.

Screenshot 2020-02-12 12.07.19

Select the appropriate Compartment in the drop-down list on the left hand side of the screen. In my previous blog post I created a separate Compartment for my Data Science work and team. Then click on the Create Projects button.

Screenshot 2020-02-12 12.09.11Enter a name for your project. I called this project, ‘DS-Demo-Project’. Click Create button.

Screenshot 2020-02-12 12.13.44

Screenshot 2020-02-12 12.14.44

That’s the Project created.

2 – Create a Notebook

After creating a project (see above) you can not create one or many Notebook Sessions.

To create a Notebook Session click on the Create Notebook Session button (see the above image).  This will create a VM to contain your notebook and associated work. Just like all VM in Oracle Cloud, they come in various different shapes. These can be adjusted at a later time to scale up and then back down based on the work you will be performing.

The following example creates a Notebook Session using the basic VM shape. I call the Notebook ‘DS-Demo-Notebook’. I also set the Block Storage size to 50G, which is the minimum value. The VNC details have been defaulted to those assigned to the Compartment. Click Create button at the bottom of the page.

Screenshot 2020-02-12 12.22.24

The Notebook Session VM will be created. This might take a few minutes. When created you will see a screen like the following.

Screenshot 2020-02-12 12.31.21

3 – Open the Notebook

After completing the above steps you can now open the Notebook Session in your browser.  Either click on the Open button (see above image), or copy the link and share with your data science team.

Important: There are a few important considerations when using the Notebooks. While the session is running you will be paying for it, even if the session got terminated at the browser or you lost connect. To manage costs, you may need to stop the Notebook session. More details on this in a later post.

After clicking on the Open button, a new browser tab will open and will ask you to log-in.

Screenshot 2020-02-12 12.35.26

After logging in you will see your Notebook.

Screenshot 2020-02-12 12.37.42

4 – Explore the Notebook Environment

The Notebook comes pre-loaded with lots of goodies.

The menu on the left-hand side provides a directory with lots of sample Notebooks, access to the block storage and a sample getting started Notebook.

Screenshot 2020-02-12 12.41.09

When you are ready to create your own Notebook you can click on the icon for that.

Screenshot 2020-02-12 12.42.50

Or if you already have a Notebook, created elsewhere, you can load that into your OCI Data Science environment.

Screenshot 2020-02-12 12.44.50

The uploaded Notebook will appear in the list on the left-hand side of the screen.

OCI Data Science – Initial Setup and Configuration

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After a very, very, very long wait (18+ months) Oracle OCI Data Science platform is now available.

But before you jump straight into using OCI Data Science, there is a little bit of setup required for your Cloud Tenancy. There is the easy simple approach and then there is the slightly more involved approach. These are

  • Simple approach. Assuming you are just going to use the root tenancy and compartment, you just need to setup a new policy to enable the use of the OCI Data Science services. This assuming you have your VNC configuration complete with NAT etc. This can be done by creating a policy with the following policy statement. After creating this you can proceed with creating your first notebook in OCI Data Science.
allow service datascience to use virtual-network-family in tenancy

Screenshot 2020-02-11 19.46.38

  • Slightly more complicated approach. When you get into having a team based approach you will need to create some additional Oracle Cloud components to manage them and what resources are allocated to them. This involved creating Compartments, allocating users, VNCs, Policies etc. The following instructions brings you through these steps

IMPORTANT: After creating a Compartment or some of the other things listed below, and they are not displayed in the expected drop-down lists etc, then either refresh your screen or log-out and log back in again!

1. Create a Group for your Data Science Team & Add Users

The first step involves creating a Group to ‘group’ the various users who will be using the OCI Data Science services.

Go to Governance and Administration ->Identity and click on Groups.

Enter some basic descriptive information. I called my Group, ‘my-data-scientists’.

Now click on your Group in the list of Groups and add the users to the group.

You may need to create the accounts for the various users.

Screenshot 2020-02-11 12.03.58

2. Create a Compartment for your Data Science work

Now create a new Compartment to own the network resources and the Data Science resources.

Go to Governance and Administration ->Identity and click on Compartments.

Enter some basic descriptive information. I’ve called my compartment, ‘My-DS-Compartment’.

3. Create Network for your Data Science work

Creating and setting up the VNC can be a little bit of fun. You can do it the manual way whereby you setup and configure everything. Or you can use the wizard to do this. I;m going to show the wizard approach below.

But the first thing you need to do is to select the Compartment the VNC will belong to. Select this from the drop-down list on the left hand side of the Virtual Cloud Network page. If your compartment is not listed, then log-out and log-in!

To use the wizard approach click the Networking QuickStart button.

Screenshot 2020-02-11 20.15.28

Select the option ‘VCN with Internet Connectivity and click Start Workflow, as you will want to connect to it and to allow the service to connect to other cloud services.

Screenshot 2020-02-11 20.17.22

I called my VNC ‘My-DS-vnc’ and took the default settings. Then click the Next button.

Screenshot 2020-02-11 20.19.31

The next screen shows a summary of what will be done. Click the Create button, and all of these networking components will be created.

Screenshot 2020-02-11 20.22.39

All done with creating the VNC.

4. Create required Policies enable OCI Data Science for your Compartment

There are three policies needed to allocated the necessary resources to the various components we have just created. To create these go to Governance and Administration ->Identity and click on Policies.

Select your Compartment from the drop-down list. This should be ‘My-DS-Compartment’, then click on Create Policy.

The first policy allocates a group to a compartment for the Data Science services. I called this policy, ‘DS-Manage-Access’.

allow group My-data-scientists to manage data-science-family in compartment My-DS-Compartment

Screenshot 2020-02-11 20.30.10

The next policy is to give the Data Science users access to the network resources. I called this policy, ‘DS-Manage-Network’.

allow group My-data-scientists to use virtual-network-family in compartment My-DS-Compartment

Screenshot 2020-02-11 20.37.47

And the third policy is to give Data Science service access to the network resources. I called this policy, ‘DS-Network-Access’.

allow service datascience to use virtual-network-family in compartment My-DS-Compartment

Screenshot 2020-02-11 20.41.01

Job Done ūüôā

You are now setup to run the OCI Data Science service.  Check out my Blog Post on creating your first OCI Data Science Notebook and exploring what is available in this Notebook.

Data Science (The MIT Press Essential Knowledge series) – available in English, Korean and Chinese

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Back in the middle of 2018 MIT Press published my Data Science book, co-written with John Kelleher. It book was published as part of their Essentials Series.

During the few months it was available in 2018 it became a best seller on Amazon, and one of the top best selling books for MIT Press. This happened again in 2019. Yes, two years running it has been a best seller!

2020 kicks off with the book being translated into Korean and Chinese. Here are the covers of these translated books.

The Japanese and Turkish translations will be available in a few months!

Go get the English version of the book on Amazon in print, Kindle and Audio formats.

https://amzn.to/2qC84KN

This book gives a concise introduction to the emerging field of data science, explaining its evolution, relation to machine learning, current uses, data infrastructure issues and ethical challenge the goal of data science is to improve decision making through the analysis of data. Today data science determines the ads we see online, the books and movies that are recommended to us online, which emails are filtered into our spam folders, even how much we pay for health insurance.

Go check it out.

Amazon.com.          Amazon.co.uk

Screenshot 2020-02-05 11.46.03

Scottish Whisky Data Set – Updated

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The Scottish Whiskey data set consist of tasting notes and evaluations from 86 distilleries around Scotland. This data set has been around a long time andwas a promotional site for a book, Whisky Classified: Choosing Single Malts by Flavour. Written by David Wishart of the University of Saint Andrews, the book had its most recent printing in February 2012.

I’ve been using this data set in one of my conference presentations (Planning my Summer Vacation), but to use this data set I need to add 2 new attributes/features to the data set. Each of the attributes are listed below and the last 2 are the attributes I added. These were added to include the converted LAT and LONG comparable with Google Maps and other similar mapping technology.

Attributes include:

  • RowID
  • Distillery
  • Body
  • Sweetness
  • Smoky
  • Medicinal
  • Tobacco
  • Honey
  • Spicy
  • Winey
  • Nutty,
  • Malty,
  • Fruity,
  • Floral,
  • Postcode,
  • Latitude,
  • Longitude
  • lat¬† — newly added
  • long¬† — newly added

Here is the link to download and use this updated Scottish Whisky data set.

The original website is no longer available but if you have a look at the Internet Archive you will find the website.

Screenshot 2020-01-23 14.44.53