Statistics and pollsters blowing the election forecast
Donald Trump's mind readers try to win him voters
Trump, Failure of Prediction, and Lessons for Data Scientists
Why FiveThirtyEight Gave Trump A Better Chance Than Almost Anyone Else
What Just Happened? by Sam Wang
Sunday, November 13, 2016
Sunday, November 6, 2016
Recent Big Data and Machine Learning Info Digest about US Election 2016/11/06
Has a computer or program predicted the result of the US Presidential elections 2016?
An artificial intelligence system that correctly predicted the last 3 elections says Trump will win
A professor who has correctly predicted elections for decades says Trump will win
Who will win the presidency? by FiveThirtyEight
Princeton Election Consortium by Sam Wang
Predicting US 2016 Presidential Election
Queensland Professor claims algorithm will accurately predict US election results
An artificial intelligence system that correctly predicted the last 3 elections says Trump will win
A professor who has correctly predicted elections for decades says Trump will win
Who will win the presidency? by FiveThirtyEight
Princeton Election Consortium by Sam Wang
Predicting US 2016 Presidential Election
Queensland Professor claims algorithm will accurately predict US election results
Labels:
AI,
Election2016,
FiveThirtyEight,
Hillary,
Queensland,
Sam Wang,
Trump
Saturday, October 29, 2016
Saturday, October 22, 2016
Recent Big Data and Machine Learning Info Digest 2016/10/22
Explaining Data Science to High School Students
Big data: Why the boom is already over
Banking, manufacturing industries will fuel demand for big data products: IDC
Kaggle Ranking #1: The Data Science (and more) of Predicting Consumer Debt Default
Preparing for the Future of Artificial Intelligence (White House)
Ask HN: How to get started with machine learning?
Big data: Why the boom is already over
Banking, manufacturing industries will fuel demand for big data products: IDC
Kaggle Ranking #1: The Data Science (and more) of Predicting Consumer Debt Default
Preparing for the Future of Artificial Intelligence (White House)
Ask HN: How to get started with machine learning?
Labels:
AI,
Big Data,
Data Science,
Hacker News,
IDC,
Machine Learning,
White House,
ZDnet
Friday, October 14, 2016
Recent Big Data and Machine Learning Info Digest 2016/10/14
Deep Reinforcement Learning: Pong from Pixels
Data Mining in Python: A Guide
Top-down learning path: Machine Learning for Software Engineers
Can we open the black box of AI?
Gartner Survey Reveals Investment in Big Data Is Up but Fewer Organizations Plan to Invest
The broken promise of open-source Big Data software – and what might fix it
Data Mining in Python: A Guide
Top-down learning path: Machine Learning for Software Engineers
Can we open the black box of AI?
Gartner Survey Reveals Investment in Big Data Is Up but Fewer Organizations Plan to Invest
The broken promise of open-source Big Data software – and what might fix it
Labels:
AI,
Andrej Karpathy,
Big Data,
Data Mining,
Deep Learning,
Gartner,
Machine Learning,
Nature,
Open Source,
Python,
Tutorial
Friday, October 7, 2016
Recent Big Data and Machine Learning Info Digest 2016/10/07
Machine Learning in a Year
Staying on Top of The Game with Modern Big Data
Why Palantir is Silicon Valley’s most questionable unicorn
What is the difference between AI, Machine Learning, NLP, and Deep Learning?
Why Deep Learning Is Suddenly Changing Your Life
Staying on Top of The Game with Modern Big Data
Why Palantir is Silicon Valley’s most questionable unicorn
What is the difference between AI, Machine Learning, NLP, and Deep Learning?
Why Deep Learning Is Suddenly Changing Your Life
Labels:
AI,
Big Data,
Deep Learning,
Machine Learning,
NLP,
Palantir
Saturday, October 1, 2016
Recent Big Data and Machine Learning Info Digest 2016/10/01
What are the major bottlenecks in making deep learning systems more effective (as of 2016)?
A Neural Network for Machine Translation, at Production Scale
Amazon's new GPU-cloud wants to chew through your AI and big data projects
Sentimental Analysis of the First Presidential Debate of 2016 Using Machine Learning
A Beginner's Guide to Apache Flink – 12 Key Terms, Explained
Announcing YouTube-8M: A Large and Diverse Labeled Video Dataset for Video Understanding Research
A Neural Network for Machine Translation, at Production Scale
Amazon's new GPU-cloud wants to chew through your AI and big data projects
Sentimental Analysis of the First Presidential Debate of 2016 Using Machine Learning
A Beginner's Guide to Apache Flink – 12 Key Terms, Explained
Announcing YouTube-8M: A Large and Diverse Labeled Video Dataset for Video Understanding Research
Labels:
AI,
Amazon,
Big Data,
Cloud,
Deep Learning,
GPU,
Hillary,
Machine Learning,
Presidential Debate,
Quora,
TensorFlow,
Translation,
Trump,
YouTube
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