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Jump in and drown in all the data

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Here is a list of data available on the internet.

“Data is the crude oil of the 21st Century, and analytics is the combustion engine.” –Gartner

I’d like to see how different people work on the same set of data:

watson visualizations



Natural Language Processing datasets at PapersWithCode.com

Computer Vision datasets at PapersWithCode.com

Speech / Voice

Speech datasets at PapersWithCode.com

Audio datasets at PapersWithCode.com


Music datasets at PapersWithCode.com

Spotify’s API was used to identify the sadest Radiohead song.


Pandora music?

Amazon music?

Computer Code

Computer Code datasets at PapersWithCode.com


Medical datasets at PapersWithCode.com


Robots datasets at PapersWithCode.com

Microsoft’s COCO

VIDEO: Joseph Redmon’s YOLO (You Only Look Once) algorithm recognizes over 80 categories of objects real-time in videos. On a laptop. Based on the University of Washington’s open-source Darknet system.

UCF YouTube Action Data Set

http://crcv.ucf.edu/data/UCF_YouTube_Action.php 11 action categories: basketball shooting, biking/cycling, diving, golf swinging, horse back riding, soccer juggling, swinging, tennis swinging, trampoline jumping, volleyball spiking, and walking with a dog.

MNIST Number Images

Instead of downloading yourself, note that the Floydhub.com has these image datasets already on their servers for Machine Learning code use:

On the website of the “Godfather of ML”, Yann Lecun)</a> is the “hello world” of deep learning – 55,000 28x28 pixel images of hand-written numbers (from 0 thru 9). Each image is labeled with the number written in the image. The “NIST” in “MNIST” is for the US National Institute of Technology.

  • this lists methods by their error rate.

  • MNIST using a “flashlight” visualization by Tensorboard by Dandelion at the TensorFlow Dev Summit Feb. 2017.

  • The MNIST dataset comes pre-loaded in Keras, in the form of a set of four Numpy arrays, loaded using this code that references two sets of data – the training set and testing set.

from keras.datasets import mnist
(train_images, train_labels), (test_images, test_labels) = mnist.load_data()

The “shape” of an array is the number of items and pixel height and width:

(60000, 28, 28)

COCO is a new image recognition, segmentation, and captioning dataset. It has 300,000 images containing multiple objects per image. 80,000 object categories.

Imagenet VGG Very Deep 19 19 weight layers pre-trained Convnet model

CALTECH 101/256 contains pictures of objects belonging to 101/256 categories

CIFAR 10/100 Subset of 80 million tiny images dataset (cats, horses, airplanes, etc.)

Cats vs Dogs Redux: Kernels Edition Dataset for Kaggle’s famous Dogs vs Cats competition

Iris Data

KONECT (the Koblenz Network Collection) from the Institute of Web Science and Technologies at the University of Koblenz–Landau collects large network datasets of all types in order to perform research in network science and related fields.


Google digitized (scanned) all the books in the 20th century and turned them into n-grams at
https://books.google.com/ngrams/ with counts how often each word occurred in all books.

Wordnet defined affect scores – a mood score.


data.gov is home to the U.S. Government’s open data. Their QA stats by department provides data quality metrics such as:

    * % Valid metadata * % Working Download URLs * % Correct Format

    Visibly missing is data from the VA and EPA, plus most agencies. us_budget has dollar outlays of each bureau within all agency (branch) of the US government, by year from 1962 to 2021.

COVID-19 Tracking Data exposed by the API, featuring hourly updates shown on CovidTracking.com.

https://parking.api.smgov.net has Santa Monica parking meters API data analyzed by http://www.memdump.io/about/ Sam Abrahams, course instructor at Metis’s Deep Learning with Tensorflow.

http://www.makeovermonday.co.uk/data has one (of 52) visualization makeover every week.

IEX (Investors Exchange) has real-time stock exchange.


Amazon Cloud

Azure - Community content are in the Cortana Gallery.

data sources ml azure cortana gallery 620x718

Google Big Data





Allen Institute (ai2) - http://allenai.org/data.html

OpenSecrets.org provides datasets related to US political campaign finance.


US Census

http://news.google.com/archivesearch has 200 years of archives


http://www.ibiblio.org/slanews/internet/intarchives.htm has links to global archives

http://searches.rootsweb.ancestry.com/ssdi.html Roots web

http://search.ancestry.com/search/db.aspx?dbid=3693 US Social Security Death Masterfile Index goes from 1935-2014

http://www.worldcat.org/default.jsp “lets you search the collections of libraries in your community and thousands more around the world.”

Maps of Geography

https://waymo.com/open from Alphabet’s (Google’s) self-driving car company Waymo has data collected by Waymo self-driving cars. As of this writing, it had 1,950 segments for 20s each, collected by high resolution LIDAR cameras at 10Hz (200,000 frames) in diverse geographies and conditions. Their code is at https://github.com/waymo-research/waymo-open-dataset

Country codes


Street Names

Zip codes by state, latitude, longitude



[*] TimeAndDate.com provides a webpage you can personalize with your favorite cities, with weather information and local time.

[?] OpenWeatherMap.org API is free and based on 40,000 crowd-sourced weather stations. *

[x] Weatherbit API

[*] AccuWeather API

[*] AerisWeather API

[x] Weather2020 API provides a 12-week forecast.

[x] ClimaCell Microweather API

[x] Weatherbit uses Machine Learning to predict weather.

[*] Metrogroup specializes in nautical data around the UK.

[*] Weatherstack in the UK.

[x] NOAA (climate.gov)

World Meteorological Organization at https://worldweather.wmo.int provides weather throughout the world, but for mostly cities.

[*] National Weather Service (weather.gov)

[*] Weather Channel (weather.com) (an IBM business)


First names registered in each state, by year, in the US from Google Big Data

Musicbase from a game

Using data

  1. Cleaning
  2. Transformation
  3. Reduction (generalize synonyms)


This is one of a series on AI, Machine Learning, Deep Learning, Robotics, and Analytics:

  1. AI Ecosystem
  2. Machine Learning
  3. Testing AI

  4. Microsoft’s AI
  5. Microsoft’s Azure Machine Learning Algorithms
  6. Microsoft’s Azure Machine Learning tutorial
  7. Microsoft’s Azure Machine Learning certification

  8. Python installation
  9. Juypter notebooks processing Python for humans

  10. Image Processing
  11. Tessaract OCR using OpenCV
  12. Amazon Lex text to speech

  13. Code Generation

  14. Multiple Regression calculation and visualization using Excel and Machine Learning
  15. Tableau Data Visualization