Recent AI, Big Data, Deep Learning, Machine Learning Info Digest 2017/10/26

AlphaGo Zero: Learning from scratch
In the paper, published in the journal Nature, deepmind team members demonstrate a significant step towards this goal.

Reimplementation of the system described in the Alpha Go Zero paper
For all intents and purposes, it is an open source AlphaGo Zero.

All the Linear Algebra You Need for AI
The purpose of this notebook is to serve as an explanation of two crucial linear algebra operations used when coding neural networks: matrix multiplication and broadcasting.

IEEE VIS 2017: Best Papers and Other Awards
This first part covers the opening, which included presentations of the best papers from all three tracks plus a new Test of Time award category.

Tech Giants Are Paying Huge Salaries for Scarce A.I. Talent
Not surprisingly, many think the talent shortage won’t be alleviated for years.

Are too many people training to become data scientists?
Definitely not. In fact, there is a major shortage of analytical talent across the board. 

Recent AI, Big Data, Deep Learning, Machine Learning Info Digest 2017/10/13

Artificial intelligence can say yes to the dress
The technology, developed by Vue.ai’s Anand Chandrasekaran and Costa Colbert, uses a machine learning approach called generative adversarial networks, or GANs. 

The History of Deep Learning — Explored Through 6 Code Snippets
In this article, we’ll explore six snippets of code that made deep learning what it is today. We’ll cover the inventors and the background to their breakthroughs. Each story includes simple code samples on FloydHub and GitHub to play around with.

China’s AI Awakening
The West shouldn’t fear China’s artificial-intelligence revolution. It should copy it.

Interview: Yoshua Bengio, Yann Lecun, Geoffrey Hinton
October 10, 2017 for the first time ever, RE•WORK brought together the ‘Godfathers of AI’ to appear not only at the same event, but on a joint panel discussion. At the Deep Learning Summit in Montreal, we saw Yoshua Bengio, Yann LeCun and Geoffrey Hinton come together to share their most cutting edge research progressions as well as discussing the landscape of AI and the deep learning ecosystem in Canada.

Deep RL Bootcamp - Lectures
August 2017   |   Berkeley CA

The Data Scientist's Guide to Apache Spark
This repo contains notebook exercises for a workshop teaching the best practices of using Spark for practicing data scientists in the context of a data scientist’s standard workflow. By leveraging Spark’s APIs for Python and R to present practical applications, the technology will be much more accessible by decreasing the barrier to entry.

Recent AI, Deep Learning, Machine Learning Study Guide 2017/09/29

15 minute guide to choose effective courses for machine learning and data science
Advice from Tirthajyoti Sarkar for young professionals in non-CS field who wants to learn and contribute to data science/machine learning. Curated from personal experience.

The Complete Guide on Learning Deep Learning
This guide by Susan Li covers almost all the courses for Deep Learning.

NVIDIA Deep Learning Institute (DLI)
The NVIDIA Deep Learning Institute (DLI) offers hands-on training for developers, data scientists, and researchers looking to solve the world’s most challenging problems with deep learning.

Meet with Harry Shum and Xuedong Huang in Seattle

During my recent trip to Seattle, I was glad to meet Harry Shum, Executive VP, Microsoft Artificial Intelligence and Research Group Group and listened to his excellent keynote speech in the 2nd North America Tsinghua Alumni Convention.

During the same convention, I also met Xuedong Huang, a Microsoft Technical Fellow in AI and Research.

I was so impressed by Dr.Huang's short presentation (most in Chinese) about Microsoft Translator in the breakout session about AI.

Recent AI, Big Data, Deep Learning, Machine Learning Info Digest 2017/09/08

Scientists Use Artificial Intelligence To Spot Alzheimer's Before Onset of Symptoms
Scientists from the Douglas Mental Health University Institute’s Translational Neuroimaging Laboratory at McGill have developed an algorithm that reliably detects signs of dementia before its onset. The technology could be used to help families prepare for treatment options, and to help researchers select better candidates for clinical trials that test drug effectiveness.

Facebook creates AI that negotiates in unknown new language
Facebook AI Research (FAIR) has been working on artificial intelligence (AI) agents that negotiate for the best deal, using all the complexities of language, reasoning, and deception that humans use.

The Seven Deadly Sins of Predicting the Future of AI
Predicting the future is really hard, especially ahead of time.

What machines can tell from your face
Life in the age of facial recognition. Technology is rapidly catching up with the human ability to read faces. In America facial recognition is used by churches to track worshippers’ attendance; in Britain, by retailers to spot past shoplifters. This year Welsh police used it to arrest a suspect outside a football game. In China it verifies the identities of ride-hailing drivers, permits tourists to enter attractions and lets people pay for things with a smile. Apple’s new iPhone is expected to use it to unlock the homescreen. 

Python overtakes R, becomes the leader in Data Science, Machine Learning platforms
While in 2016 Python was in 2nd place ("Mainly Python" had 34% share vs 42% for "Mainly R"), in 2017 Python had 41% vs 36% for R. 

Object detection: an overview in the age of Deep Learning
There’s no shortage of interesting problems in computer vision, from simple image classification to 3D-pose estimation. One of the problems we’re most interested in and have worked on a bunch is object detection. 

Background removal with deep learning
Background removal is a task that is quite easy to do manually, or semi manually (Photoshop, and even Power Point has such tools) if you use some kind of a “marker” and edge detection.  However, fully automated background removal is quite a challenging task.

Recent AI, Big Data, Deep Learning, Machine Learning Info Digest 2017/09/01

The Rise of the Data Engineer
Over the past 5 years working in Silicon Valley at Airbnb, Facebook and Yahoo!, and having interacted profusely with data teams of all kinds working for companies like Google, Netflix, Amazon, Uber, Lyft and dozens of companies of all sizes, Maxime Beauchemin is observing a growing consensus on what “data engineering” is evolving into, and felt a need to share some of my findings.

The Downfall of the Data Engineer
In this post, Maxime Beauchemin want to expose the challenges and risks that cripple data engineers and enumerates the forces that work against this discipline as it goes through its adolescence.

Machine Learning for Humans
Simple, plain-English explanations accompanied by math, code, and real-world examples by Vishal Maini.

How Machines Learn: A Practical Guide
Karlijn Willems lists seven steps (and 50+ resources) that can help you get started in this exciting field of Computer Science, and ramp up toward becoming a machine learning hero.

How AI can aid, not replace, humans in recruitment
One industry where the use of the technology is being actively explored is recruitment, where enterprises are drawing on its capabilities in various ways to help them find new staff.

Report shows that AI is more important to IoT than big data insights
We think that big data is the only thing we need for all of our insights. But in the world of Internet of Things (IoT), that is not the case.

Four deep learning trends from ACL 2017 (part 1)
Four deep learning trends from ACL 2017 (part 2)
In this two-part post, Abigail See describes four broad research trends that she observed at the conference (and its co-located events) through papers, presentations and discussions. The content is guided entirely by her own research interests; accordingly it’s mostly focused on deep learning, sequence-to-sequence models, and adjacent topics. 

Deep Learning And Reinforcement Learning Summer School 2017
Slides: https://mila.umontreal.ca/en/cours/deep-learning-summer-school-2017/slides/
Video: http://videolectures.net/deeplearning2017_montreal/

Recent AI, Big Data, Deep Learning, Machine Learning Info Digest 2017/08/25

Designing a Deep Learning Project 

The Present and Future of Quantum Computing for AI
Quantum computing is still in it’s infancy, and no universal architecture for quantum computers exists right now. However, their prototypes are already here and showing promising results in cryptography, logistics, modelling and optimization tasks. For AI researchers optimization and sampling is particularly important, because it allows to train Machine Learning models much faster with higher accuracy.

Artificial intelligence could be the future of banking
By leveraging AI, banks can engage with consumers in a faster and more consistent manner. They can use “bots” at contact centres for basic inquiries to free up employees for more complicated questions. They can use robo-advisers to provide basic investment services at lower cost.

New app scans your face and tells companies whether you’re worth hiring
HireVue, a company with a “video interview intelligence platform,” wants to make that easier by using artificial intelligence to do the heavy lifting for you and screen multiple candidates at once.

Pandas tips and tricks
This post includes some useful tips for how to use Pandas for efficiently preprocessing and feature engineering from large datasets.

The Hard Thing About Machine Learning
Building systems is hard; building machine learning systems that give robust predictions is especially hard.

Aug. 2017 Hive User Group Meeting @HortonWorks
1. Hive on Spark, production experience @Uber (Xuefu Zhang)
2. Reair and its usage for Uber's multi data center replication (Zheng Shao)
3. ACID, use cases in data management (Carter Shanklin)
4. Optimized Hive replication (Anishek Agarwal)
5. LLAP: Locality is dead (in the cloud) (Gopal Vijayaraghavan)
6. Don't reengineer, reimagine: Hive buzzing with Druid's magic potion (Slim Bouguerra)