compared to the previous posts this post is very rough and messy. When time permits I will clean it up.
Here below are a few lists associated with my personal learning about the academic field of AI and its related fields.
I am not an expert in this field; rather the contrary. I am interested in considering questions related with bringing technology literacy into the thinking of educators and learners within the K-12 realm. The resources below and elsewhere here in this blog are mainly catered to high school (or those beyond). If some resources seem too advanced, they were added to show where one could aim to learn toward or where one could end up if one continued studies in this area. Therefore, some resources are technical while others are not.
This post includes a name list. It is a list of what I understand to be leading voices in the field. Secondly, there is a bibliography of works I found online or offline.
I superficially or more profoundly browsed these , in search of a better understanding and contextualization (in a historical and trans-disciplinary setting).
Where found and available URLs are offered. Some additional or the same URLs or references can be found in other posts (see the one on mathematics and the field of AI, to name but one).
Lastly, a list of URLs to data sets is included at the end of this post.
As a
young learner on your educational path and as a young participant in your
community you might like to find some references that can give you an idea or that
can ignite your imagination of how and where and with whom to walk your path
towards growing into tomorrow’s AI expert.
We
learn on our own but better even by the guidance of others and by observing and
learning from what they have done or are doing.
Here
below is a list of historical figures and present-day scholars. The list is
surely not complete and needs continued updating. The list does not imply a
preference imposed by the author. It tries to highlight a few scholars from
around the world, scholars from within China and scholars that are in pure
academic research as well as in innovation and entrepreneurial areas. More
scholars and innovators, involved in important work in the field of AI, are
missing than those listed. It also is incomplete as to what all the work is
that these experts have been involved in up till now. The list does however
give you a spark, a hint and points you in directions you can further explore
by means of your own research and study.
Maybe
you can add a few names to this list. Perhaps one day your work will be a
beacon as well for another young learner.
- Mathematician and one of the most important
logisticians.
- His work lies at the mathematical and logical
foundation of, for instance, Turing’s work.
- [2] on
“intelligence explosion,”[3] that
are claimed to have led to today’s hypothetical concept of the “technological singularity”.[4]
Similar to this present-day hypothesis, Dr. Good envisioned a potential future
creation, in the likes of what we now call the future-existence of an
Artificial General Intelligence agent, (AGI), that would be able to solve human
concerns and that would far outweigh human (intellectual) ability. He felt it
stood to reason that it would be the last invention humans had to make.[5]
- 1929-2015
- While
suggested by Turing[6],
he pioneered Genetic Algorithms with other scientists such as Dr. GOLDBERG,
David Edward.
- Inventor of the LISP programming language, used
in the early research and development of AI systems
- Co-founder of the academic field of Artificial
Intelligence
- Invented the term “Artificial Intelligence”
- Co-founder of The MIT Artificial Intelligence
Lab
- Leading voice on and pioneer in Artificial
Intelligence
- Built the first neural network learning machine
in 1951
- A pioneer in computer gaming and AI
- He put the term and the research surrounding
“Machine Learning” on the map in the 1950s and with his paper: “Some Studies in Machine Learning Using the
Game of Checkers“. IBM Journal of Research and Development. 44:
206–226
- ·
STRACHERY, Christopher
- By many referred to as the father of Artificial
Intelligence.
- Created fundamental theories of Computation and
in Computer Science; e.g. the idea of the binary digital language of ones and
zeroes, the (theoretical) Turing Machines
- Created the Turing Test allowing to see whether
or not a machine showcased intelligent behavior[8]
- Created the first electronic computer
- [blablabla]
- Most computers, as we know them today, are based
on his conceptualizations.
- Dr. WÁNG Hào (王浩)(1921 – 1995)
- Tsinghua University graduate
- Mathematician,
philosopher and logistician.
- Proved hundreds of mathematical theories
with a computer program written in 1959
- Inventor of the Wang Tiles; proved that
any Turing Machine can be turned into Wang Tiles.
- Inventor of a number of computational
models.
- Dr. ZADEH, Lotfi
Aliasker (1921 – 2017)
- AI
researcher, mathematician, computer scientist
- Inventor[9]
of Fuzzy Mathematics, Fuzzy Algorithms, Fuzzy Sets, Fuzzy Logic and so on. Over-simplified, Fuzzy logic is a
generalization of Boolean logic and a form of many-value logic, with values
in-between 0 and 1 (whereas traditionally, logic operates with values that are
either on or off; one or zero; right or wrong).
Mini Project #___ : Inspiration by Following the Old Masters
- Which of these figures or their work are you
most inspired by? Why?
- Can you find some other historical figures
associated with research & developments (R&D) in AI whom you are
inspired by?
The following is an incomplete list composed as of January
2020. Please note, more experts or leading voices are mentioned across the text
chapters (e.g. see footnotes and references; see section 05 of this text). The
author apologizes to any expert or leading voice that might not yet be
represented or that might be inaccurately represented here. Pease contact the
author so that refinements can be added. The aim is to give young learners some
sort of direction, motivation, hints and passion for the field of AI. Thank you
for your support:
- ·
Dr.
BENGIO, Yoshua: Research into
Artificial Neural Networks, Unsupervised Machine Learning and Deep Learning
- ·
Dr.
BLEI, David M.: research in Machine Learning, Statistical Models (e.g.
Topic Modeling), algorithms, and related topics.
- ·
Dr.
BOSTROM, Nick: Research in ethics surrounding Artificial
Superintelligence.
- ·
Dr.
BREASEAL, Cynthia: Research in Human-Robot Interaction.
- ·
Dr.
BRYSON, Joanna: Research in AI ethics and in AI systems
helping to understand biological intelligence
- ·
Dr.
Chén Dānqí 陈丹琦: a Tsinghua
& Stanford Universities graduate. Assistant Professor at Princeton
University. Main field of research in Natural Language Processing (NLP).
-
Graduate from and Professor at
the Institute of Computing Technology, Chinese Academy of Sciences. Selected by MIT Technology Review as one of the 2015 top 35 innovators under 35
years old. Research and developments in large-scale Machine Learning solutions,
Deep Learning, reduction of energy requirements or computational costs, brain-inspired processor chips, and
related topics.
- ·
Dr. DUAN Weiwen: AI Director
of the Department of Philosophy of Science and Technology, The Institute of
Philosophy, The Chinese Academy of Social Sciences (CASS). He specializes,
among others, in ignorance in sciences, philosophy of IT, Big Data issues, and
Artificial Intelligence. Dr. Duan is the deputy chairman of the Committee of
Big Data Experts of China. His research is supported by the National Social
Sciences Fund of China (NSSFC).
- Research
and developments in Emotional AI,
subtle expression recognition, facial recognition. Entrepreneur in related AI developments.
- ·
Dr.
ERKAN, Ayse Naz: Research in Content Understanding &
Applied Deep Learning.
- ·
Dr.
FREUND, Yoav: Research and advances in algorithm design,
Machine Learning and probability theory.
- ·
Dr. FUNG, Pascale馮雁: leading researcher in Natural Language
Processing.
- Research on Human-centered AI, autonomous
vehicles, Deep Learning, robotics
-
Research on algorithm design, Bayesian Machine Learning, Computational
Neuroscience, Bioinformatics, Statistics and other areas.
- ·
Dr. GOERTZEL, Ben Research on and developments in AGI and
robotics.
- Research and developments in Machine Learning and Deep Learning
- Neuroscientist. Research and developments in
Artificial General Intelligence (AGI), Machine Learning (AlphaGo) and related
topics.
- ·
Dr.
HINTON, Geoffrey E:
Leading AI academic, computer scientist and cognitive psychologist with
a focus on artificial neural networks. The great-great-grandson of the logician
George Boole ( who’s work on, among others, algorithms for logic deduction, is
still of computational importance). Dr. Hinton is considered one of the most
prominent pioneers in Deep Learning.
- ·
Dr. HUTTER, Marcus. researching
the mathematical foundations of AI and Reinforcement Learning; leading
authority on theoretical models of super intelligent machines.
- Trained Dr. Ng and other leading scholars in
the field of AI. Research in Machine Learning, recurrent neural networks,
Bayesian networks in Machine Learning and other links between Machine Learning
and statistics
- ·
Dr. KARPATHY, Andrej: Research on
Deep Learning in Computer Vision, Generative Modeling, Reinforcement Learning,
Convolutional Neural Networks, Recurrent Neural Networks, Natural Language
Processing
- Research on Artificial Intelligence (e.g.
Learning platforms for humans; Content recommendation, etc.)1
- ·
Dr.
KURZWEIL, Ray: a legendary authority on AI and thinker on
the technological singularity
- ·
Dr.
LAFFERTY, John D.: Research in Language and graphic models, semi supervised
learning, information retrieval, speech recognition.
- ·
Dr.
LECUN, Yann: Research in computational neuroscience, Machine
Learning, mobile robotics, and computer vision. Developed the ‘Convolutional Neural Networks’ (a model of image recognition mimicking
biological processes)
- ·
Dr.
LI Fei-fei: AI scientist & Machine Learning expert
with a focus on computational neuroscience, image / visual recognition and Big
Data. Pushed the collection and creation of large quality datasets and this
towards the improvement of algorithm design. The result was ImageNet,
containing more than 10million hierarchically organized images.
- ·
Dr.
LI Kāifù: research on Machine Learning and pattern
recognition. The world’s first speaker-independent, continuous speech
recognition system; investor in mainly China’s AI R&D; Chairman of the
World Economic Forum’s Global AI Council; author on AI and a leading force in
supporting the training of AI-related engineers in China.
- ·
Dr. LI, Sheng李生 : leading
research on Natural Language Processing (NLP) and one of China’s pioneers in
this field. Graduate from and professor at the Harbin Institute of Technology
(HIT). President of Chinese Information Processing Society of China (CIPSC).
- Former President of Beihang University and
Professor of Computer Science at the Beihang University. Co-lead China’s
National Engineering Laboratory of Deep Learning. Research in AI and network
computing.
- ·
Dr.
LIM, Angelica: robotic development & human-styled
learning
- ·
Dr.
LIN Dekang: A Tsinghua University graduate. Senior research scientist
in Machine Learning, Natural Language Processing and more at a major AI lab.
- ·
Dr.
LIN Yuanqing: A Tsinghua University graduate. Research and developments
in AI, Big Data, Deep Learning,
- ·
Dr. LIU, Ting (刘挺): research and development
in the area of Natural Language Processing.
- Fudan University graduate. Leading AI researcher and
developer with a focus on autonomous driving and other aspects in the field of
AI. Leadership in related industry.
- ·
Dr.
MARCUS, Gary: Research on natural
and artificial intelligence in areas of psychology, genetics and neuroscience.
- ·
Dr.
McCALLUM, Andrew: Research in Machine Learning (i.e. Semi
Supervised Learning, natural language processing, information extraction,
information integration, and social network analysis)
- ·
Dr.
MIN Wanli: A University of
Science & Technology of China graduate. Research and developments in AI
applications, traffic pattern recognition, Machine Learning and related
aspects.
- AI researcher, famous AI educator, worked on
autonomous helicopters, Artificial Intelligence for robots and created the
Robot Operating System (ROS). Research in Machine Learning (Reinforcement
Learning, Supervised Learning, …). IS also well-known for his online course
material.[10]
- ·
Dr.
Oliphant, Travis: Scientific Computing developer. Created
NumPy, SciPy and Numba. Founded Anaconda and more
- Data
Scientist. Research in
Big Data, Data Mining and Machine Learning. Editor of KDnugget (a source for
Data Science and Machine Learning).
- Research in AI in self-driving vehicles
- ·
Dr.
RUS, Daniela L.: research in self-reconfiguring distributed
and collaborative robots (e.g. autonomous swarms), autonomous
environment-adaptable shape-shifting machines (this is of use where conditions
cannot be foreseen and therefore cannot be hard-coded)
- ·
Dr.
RUSSELL, Stuart J.: author of the most cited book (together with Dr. NORVIG,
Peter) on AI which is also used in about 1300 universities, across about 116
countries as AI course material. He did research on inductive and analogical
reasoning. He founded the Center for Human-Compatible Artificial Intelligence
- ·
Dr.
SCHMIDHUBER, Jurgen: AI scientist with a focus on and
self-improving AI and (recurrent) neural networks, used for speech
recognition. He works on AI for finance and autonomous vehicles.
- ·
Dr.
SCHöLKOPF, Bernhard: Research in Machine Learning, Brain-computer interfaces,
and other related areas,
- ·
Dr.
SHAPIRE, Robert: Research and Developments in Machine
Learning, Decision Trees, Game Theory.
- ·
Dr.
SHEN Xiangyang; Industry
leader in Research and Development in the field of Artificial Intelligence.
- AI scientist with a focus on learning. One
of the creators behind the AI method known as modern Computational
Reinforcement Learning.
- ·
Dr.
SWEENEY, Latanya: Research in the area of biases in Machine
Learning algorithms
- ·
Dr.
TANG Xiaoou: Research in computer vision, pattern
recognition, and video processing. A leading entrepreneur.
- ·
Dr.
TEGMARK, Max: Investigates existential risk from advanced artificial
intelligence
- ·
Dr.
WHYE, Teh Yee: Research in Machine Learning (Deep Learning), Statistical
Machine Learning and Face Recognition.
- ·
Dr.
THRUN, Sebastian: Research in Machine Learning, autonomous vehicles,
probabilistic algorithms, robotic mapping.
- ·
Dr.
VALIANT, Leslie: research and advances in computational
theory, complexity theory, algorithms and machine learning.
- ·
Dr. VAPNIK, Vladimir: Research in
the area of Machine Learning and Statistical Learning. Co-invented the
Support-Vector Machine Method
- Research in
the area of Machine Learning, Deep Learning and Reinforcement Learning
- 王海峰: a Harbin Institute of Technology graduate. Leadership in AI developments with foci on
Deep Learning, Big Data, computer vision, Natural Language Processing (NLP),
machine translation, speech recognition, personalized recommendations, and so on.
- ·
Dr.
WU Hua: A graduate from the Chinese Academy of
Sciences. Cutting-edge breakthroughs in Conversational AI & Natural
Language Processing (NLP), dialog systems, Neural Machine Translation and
related topics.
- ·
Dr.
XU Wei: A Tsinghua University graduate. Received the title of “Distinguished Scientist”. Research and
developments in areas of Deep Learning, image classification, autonomous
vehicles, translation processes, and so on,
- ·
Dr.
YANG Yiming: Research in Machine Learning
- ·
Dr.
YE Jieping: A Fudan University graduate. Research and developments in
Big Data, Data Mining, Machine Learning, autonomous vehicles, and so on.
- ·
Dr.
YU Dong: A Zhejiang University graduate. Research and developments
in Speech recognition, Natural Language Processes, natural language
understanding, and related topics.
- ·
Dr.
YU Kai: a Nanjing University graduate. Research and developments
in Deep Learning, pervasive AI hardware systems, facial recognition, automatic
ordering, driver-assistant systems, and related areas.
- ·
Dr. ZADEH, Reza: Research on
Discrete Applied Mathematics, AI, Machine Learning
- Research on
technical models for Brain-inspired AI, AI Ethics and Governance. Professor and
Deputy Director at Research Center for Brain-inspired Intelligence (RCBII),
Institute of Automation, Chinese Academy of Sciences. He is Director for the
Research Center on AI Ethics and Governance, Beijing Academy of Artificial
Intelligence. Dr. Zeng is a board member for the National Governance Committee
for the New Generation Artificial Intelligence, Ministry of Science and
Technology China.
- A Hefei University of Technology graduate. Professor of Machine Learning at the Peking
University (aka Beida; 北京大学, PKU). Former
Vice Dean of the School of EECS. Research in Machine Perception,
computer vision and other related areas.
- ·
Dr.
ZHANG Bo: Co-leads China’s National Engineering Laboratory of Deep
Learning. A member of the member of the Chinese Academy of Sciences. A graduate
from and Professor at Tsinghua University. Research in Machine Learning, neural
networks, task and motion planning, pattern recognition, image retrieval and
classification, and other areas.
- ·
Dr. ZHANG, Min张民: research and
development in the area of Natural Language Processing at the Soochow
University (in Sūzhōu, Jiāngsū Province, P.R. China; Sūzhōu Dàxué, 苏州大学).
- 张潼). Research focus on Machine Learning
algorithms and theory, statistical methods for big data and their applications,
computer vision, speech recognition, Natural Language Processing, and so on.
- ·
Dr ZHAO, Tiejun (赵铁军): research and
development in the area of Natural Language Processing.
- Graduated from 3 Chinese universities:
Northeastern University, Beihang University and the Chinese Academy of
Sciences, Institute of Automation. Conducts research on Machine Learning and
Explainable AI at one of the front-running labs in AI development.
- ·
Dr.
ZHOU Jingren: A graduate from the University of Science
and Technology of China. Research and Developments in AI, Big Data, large scale
Machine Learning, Speech and Language Processing, image & video processing,
and so on.
- ·
Dr.
ZHOU, Ming: cutting edge research and
development in the area of Natural Language Processing.
- Doctor of Science at the Chinese Academy of
Sciences. Research and Developments in ChatBots, conversational interfaces, and
related areas.
Mini Project #___: Inspiration from Following Today’s Masters
- Which of these figures or their work are you
most inspired by? Why?
- Can you find some more details and up-to-date
information about your chosen role model?
- Can you find some other leading figures you are
inspired by that are also working in the field of AI and that are not (yet) in
this list?
- Can you figure out how your choice of leading
figures relates to AI and to other researchers by creating an
Entity-Relationship Model (see example here)?
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[2] Good,
I.J. (1965). Speculations Concerning the
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(1966). Advances in Computers Vol.6:
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[3] Bostrom. N. (2014). Superintelligence: Paths, Dangers, Strategies. Oxford: Oxford
University Press
[4] Shanahan, M. (2015). The Technological Singularity. The MIT Essential Knowledge Series.
Cambridge, MA: The
MIT Press.
[5] Good, I.J. (1965). p.33
[6] Turing, A. M. (October, 1950). “Computing Machinery and Intelligence”
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[7] Robinson, John Alan (January 1965). A
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[10] An example of Dr. Ng’s online course material: https://www.coursera.org/learn/machine-learning
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Additionally, an incomplete list of online data sets:
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Data set location
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area
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http://cricsheet.org/downloads/
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http://usfundamentals.com/download
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http://www.sports-reference.com/
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http://yann.lecun.com/exdb/mnist/
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https://data.world/
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https://dev.twitter.com/streaming/overview
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https://stocktwits.com/developers/docs
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https://www.ehdp.com/vitalnet/datasets.htm
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https://www.quandl.com/data/FRED/documentation/documentation
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https://www.quandl.com/data/WIKI/documentation/bulk-download
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https://www.quandl.com/open-data
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https://www.quantopian.com/data
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https://github.com/awesomedata/awesome-public-datasets
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Agriculture, biology, climate, weather, earth
sciences, economics, education, energy, finance, healthcare, …
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http://datamarket.azure.com/browse/data?price=free
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Agriculture, weather and so on
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https://openlibrary.org/developers/dumps
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Book library data sets
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137.189.35.203/WebUI/CatDatabase/catData.html
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Cat images
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https://archive.org/details/2015_reddit_comments_corpus
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Chat data set
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https://developer.twitter.com/en/docs/tweets/search/overview
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Chats-related content data
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https://developers.facebook.com/products/instagram/
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Chats-related content data
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https://dataportals.org/search
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Civil, country, etc.
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http://gcmd.nasa.gov/
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earth sciences and environmental sciences
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https://nces.ed.gov/
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Education data sets
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https://nces.ed.gov/
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education demographics in the USA and the world
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http://www.mlopt.com/?p=6598
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Electric Vehicle recharge points dataset from
Northern Ireland and Republic of Ireland
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http://www.cs.cmu.edu/~enron/
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Email text as data set
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http://open-data.europa.eu/en/data/
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EU civil data sets
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https://data.europa.eu/euodp/en/home
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EU civil, social
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https://opendatamonitor.eu/frontend/web/index.php?r=dashboard%2Findex
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European data sets
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http://vis-www.cs.umass.edu/lfw/
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Faces data set
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http://www.imdb.com/interfaces/
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Film data
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http://www.bfi.org.uk/education-research/film-industry-statistics-research
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Film data (UK)
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https://markets.ft.com/data/
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finance
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https://www.imf.org/en/Data
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finances, debt rates, foreign exchange
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https://cmu-perceptual-computing-lab.github.io/foot_keypoint_dataset/
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Foot Keypoint Dataset (Carnegie Mellon University)
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https://opencorporates.com/
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Global database of companies
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https://trends.google.com/trends/
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Global internet searches
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https://comtrade.un.org/
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Global trade
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http://yann.lecun.com/exdb/mnist/
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handwritten digits examples, and a test set of 10,000
examples
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https://www.data.gov/health/
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Health (USA)
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http://data.nhm.ac.uk/
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historical specimens in the London museum
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https://www.glassdoor.com/developer/index.htm
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Human resource related data sets
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https://archive.org/details/audio-covers
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image processing research data set
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https://archive.ics.uci.edu/ml/datasets/Iris
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Iris flowers data set. This is claimed to be one of
the better freely available classification sets. It is used in the beginners
project on Machine Learning and classification.
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https://www.bjs.gov/index.cfm?ty=dca
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law enforcement in the USA
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http://www.londonair.org.uk/london/asp/datadownload.asp
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London air quality data
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http://archive.ics.uci.edu/ml/datasets.php
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Machine Learning
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http://archive.ics.uci.edu/ml/
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Machine Learning data sets
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http://mldata.org/
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machine learning datasets for training systems
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http://www.msmarco.org/
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machine learning datasets for training systems in
reading comprehension and question answering
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https://aws.amazon.com/datasets/million-song-dataset/
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Music data set
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https://opendata.cityofnewyork.us/
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New York City data sets
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https://data.worldbank.org/data-catalog/health-nutrition-and-population-statistics
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Nutrition, health, population
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|
https://go.developer.ebay.com/ebay-marketplace-insights
|
Online sales datasets (mainly USA)
|
|
|
http://opendata.cern.ch/
|
particle physics experiments data
|
|
|
https://exoplanetarchive.ipac.caltech.edu/
|
planets and stars
|
|
|
https://data.worldbank.org/
|
population demographics, economics
|
|
|
https://www.qlik.com/us/products/qlik-data-market
|
population, currencies
|
|
|
https://deepmind.com/research/open-source/kinetics
|
pose and action data sets
|
|
|
http://fivethirtyeight.com/
|
public opinion on sport and more
|
|
|
https://www.google.com/publicdata/directory
|
public-interest data (USA)
|
|
|
https://scholar.google.com/
|
Scholarly text as data sets
|
|
|
https://science.mozilla.org/projects
|
Sciences
|
|
|
https://cooldatasets.com/
|
Sciences, civil, entertainment, machine learning,
etc.
|
|
|
https://www.ukdataservice.ac.uk/
|
social, economic population in the UK
|
|
|
http://www.databasesports.com/
|
Sports data
|
|
|
https://data.gov.uk/
|
UK civil, social
|
|
|
https://data.unicef.org/
|
UNICEF data sets, civil
|
|
|
http://data.un.org/
|
United Nations data sets
|
|
|
http://data.humdata.org/
|
United Nations humanitarian data sets
|
|
|
https://archive.ics.uci.edu/ml/index.php
|
University of California Machine Learning dataset
|
|
|
https://lodum.de/
|
University of Münster data sets
|
|
|
https://www.data.gov/
|
USA civil, social
|
|
|
https://ucr.fbi.gov/
|
USA crime statistics
|
|
|
http://www.census.gov/data.html
|
USA population
|
|
|
https://www.yelp.com/dataset
|
User data sets, (Yelp users)
|
|
|
http://opendataimpactmap.org/
|
Various
|
|
|
http://plenar.io/
|
Various
|
|
|
https://ckan.org/
|
Various
|
|
|
https://datahub.io/search
|
Various
|
|
|
https://dataverse.org/
|
Various
|
|
|
https://github.com/datasets/
|
various
|
|
|
https://knoema.com/
|
various
|
|
|
https://opendatakit.org/
|
Various
|
|
|
https://opendatamonitor.eu/frontend/web/index.php?r=dashboard%2Findex
|
Various
|
|
|
https://registry.opendata.aws/
|
Various
|
|
|
https://rs.io/100-interesting-data-sets-for-statistics/
|
various
|
|
|
https://www.columnfivemedia.com/100-best-free-data-sources-infographic
|
Various
|
|
|
https://www.kaggle.com/datasets
|
Various data sets
|
|
|
https://github.com/freeCodeCamp/open-data
|
Various for coders
|
|
|
http://datahub.io/
|
Various open data sets
|
|
|
https://www.kaggle.com/
|
Various, general data resource
|
|
|
https://www.reddit.com/r/datasets/comments/exnzrd/coronavirus_datasets/
https://github.com/CryptoKass/ncov-data
|
Virus data set
|
|
|
https://wiki.dbpedia.org/
|
Wikipedia data sets
|
|
|
https://www.who.int/gho/database/en/
|
World Health Organization data sets
|
|
|
https://cdan.dot.gov/query
https://github.com/wgetsnaps/ftp.nhtsa.dot.gov–fars
|
Traffic, USA, fatality data set
|
|
|
http://www.image-net.org/
|
Images as huge quality dataset
|
|
|
http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.296.9477&rep=rep1&type=pdf
|
|
|
|
http://xiaming.me/posts/2014/10/23/leveraging-open-data-to-understand-urban-lives/
|
New York (civil) data sets and more
|
