In the first part of this series, I introduced the Outbrain Click Prediction machine learning competition. That post described some preliminary and important data science tasks like exploratory data analysis and feature engineering performed for the competition, using a Spark cluster deployed on Google Dataproc. In this post, I describe the competition evaluation, the design of my cross-validation strategy and my baseline models using statistics and trees ensembles. In that competition, Kagglers were required to rank recommended ads by decreasing predicted likelihood of being clicked. Sponsored search advertising, contextual advertising, display advertising and real-time bidding auctions have all relied heavily on the ability of learned models to predict ad click–through rates (CTRs) accurately, quickly and reliably.

A fresh scrape from Glassdoor gives us a good idea about what applicants are asked during a data scientist interview at some of the top companies. Unfortunately for us, almost every company has their interviewees sign NDAs. Since Glassdoor allows anonymity, a few brave souls have given us some fantastic examples of what they were asked during the interview process at top companies like Facebook, Google, and Microsoft. If you find yourself unable to answer some of the questions below, consider checking out a course or a book on the subject. If you'd like to share your answer(s) to any of the questions, leave a comment and I'll add the top ones to the post.

Deep-learning systems, which use artificial networks modelled on the human brain, tend to only able to do one task at a time. But now, for the first time, Google has created a system that can do eight tasks at once, including image and speech recognition and language translation. The research suggests that AI could be taught to multitask in the future and become more like humans in the way they think. The network is capable of learning eight different tasks simultaneously. It can detect objects in images, provide captions, recognise speech, translate between four pairs of languages, and do grammatical constituency parsing at the same time.

SYS-CON Events announced today that TMC has been named "Media Sponsor" of SYS-CON's 21st International Cloud Expo and Big Data at Cloud Expo, which will take place on Oct 31 - Nov 2, 2017, at the Santa Clara Convention Center in Santa Clara, CA. Global buyers rely on TMC's content-driven marketplaces to make purchase decisions and navigate markets. Learn how we can help you reach your marketing goals. With major technology companies and startups seriously embracing Cloud strategies, now is the perfect time to attend 21st Cloud Expo, October 31 - November 2, 2017, at the Santa Clara Convention Center, CA, and June 12-14, 2018, at the Javits Center in New York City, NY, and learn what is going on, contribute to the discussions, and ensure that your enterprise is on the right path to Digital Transformation. Every Global 2000 enterprise in the world is now integrating cloud computing in some form into its IT development and operations.

I've split this post into four sections: Machine Learning, NLP, Python, and Math. For future posts, I may create a similar list of books, online videos, and code repos as I'm compiling a growing collection of those resources too. What's the Difference Between Artificial Intelligence, Machine Learning, and Deep Learning?

Which machine learning algorithm should I use?

To understand human consciousness, we need to know why it exists in the first place. New experimental evidence suggests it may have evolved to help us learn and adapt to changing circumstances far more rapidly and effectively. We used to think consciousness was a uniquely human trait, but neuroscientists now believe we share it with many other animals, including mammals, birds and octopuses. While plants and arguably some animals like jellyfish seem able to respond to the world around them without any conscious awareness, many other animals consciously experience and perceive their environment. In the 19th century, Thomas Henry Huxley and others argued that such consciousness is an "epiphenomenon" – a side effect of the workings of the brain that has no causal influence, the way a steam whistle has no effect on the way a steam engine works.

The world around us is becoming increasingly automated, with many of us leaning on digital assistants such as Cortana, Echo and Siri to run our lives. Before too long it is highly likely that our cars will be driverless, fridges will restock automatically and our homes will heat themselves. Recently, Westworld - the sci-fi thriller about a technologically advanced, Western-themed amusement park populated by androids that malfunction and begin killing the human visitors - became the biggest watched show of all time on Sky Atlantic. Could this fiction be closer to reality than many of us would care to admit? Our recent study asked this question, and for almost two-thirds of respondents, the answer is yes.

Lee Se-dol (L), one of the greatest modern players of Go, at a post-match press conference after being beaten by Google's DeepMind AI computer in March. Deep Instinct co-founder and Chief Technology Officer Eli David says the day when a computer is as smart as a human, or smarter, may be a lot closer than many think. AI programs, "are on an accelerating path of growth in their capabilities. In the near future, they will reach near human or superhuman capabilities," David told me in an interview. As AI gets smarter, it's crucial to stay ahead of criminals and terrorists.

The chatbot is the new black: exponentially growing in popularity as the world becomes an increasingly connected place. And as we trundle along this path towards nirvana where everything and everyone is connected, all the time, we'll grow more and more comfortable with interacting with these machines online. Inevitably chatbots and artificial intelligence (AI) will dominate the online landscape and be involved with almost everything we do online. While most chatbot tasks are quite basic at the moment, continued innovation in AI technology means that they're getting smarter and smarter. Some research suggests that only about one-third of all customer service queries will require human attention.