With 60 percent of businesses across the globe expected to use A.I. by 2018, South African companies are championing how machine learning can manage business operations Artificial intelligence, or A.I., is already used by 39 percent of businesses around the globe in some form, according to Sage's latest analysis. Be it to scan and organise vast amounts of data quickly to free up an employee for other tasks, or to help a customer answer common questions on a website, A.I. uses programmed requirements and machine learning to reduce the time taken to complete mundane tasks, improving business efficiency and operating costs. Yet, despite CNBC reporting that smart technology boosts productivity, many companies are still to factor A.I. into their business model. Fortunately, South African companies are leading the way by adopting machine learning programmes to increase efficiency in numerous areas of their businesses. With the internet opening new opportunities for employers to hire highly skilled workers from all over the world, as well as the ability to post job postings to websites and social media, businesses are receiving more résumés and CVs than ever before.

Last month we reported on the results of 18th annual KDnuggets Software Poll: New Leader, Trends, and Surprises in Analytics, Data Science, Machine Learning Here is a more detailed look at which tools go well with each other, and which don't. We also find an emerging Python-friendly ecosystem of tools that are commonly used with the two leading edges of data science: Big Data (Spark/Hadoop) and Deep Learning. A link to anonymized dataset is at the end of this post - analyze the data yourself and publish or send me the results.

As if the AI skill shortage wasn't bad enough, universities are losing teachers and students to companies offering unmatchable benefits. Last week, our sister publication Developer reported AI skills are in such high demand that companies are willing to offer six figure salaries. Universities are unable to match these benefits and it's creating a brain drain preventing the current lack of AI talent problem from being addressed. The Guardian reports of a case from Imperial College London where a senior professor couldn't understand why one of her students was not turning up to any classes. Most people wouldn't pay £9,250 per year in tuition fees only to not turn up.

WHAM-TV reports McQuaid Jesuit High School held a ceremony Wednesday for the new Wegman Family Science and Technology Center. The 36,000-square foot center includes advanced robotics rooms and state-of-the-art science labs. McQuaid's robotics and Lego robotics teams will also have their own spaces in the STEM wing.

The majority of employed data scientists gained their skills through self-learning or a Massive Open Online Course (MOOC) rather than a traditional computer science degree, according to a survey from data scientist community Kaggle, which was acquired by Google Cloud earlier this year. Some 32% of full-time data scientists started learning machine learning or data science through a MOOC, while 27% said that they began picking up the needed skills on their own, the 2017 State of Data Science & Machine Learning Survey report found. Some 30% got their start in data science at a university, according to the survey of more than 16,000 people in the field. More than half of currently employed data scientists still use MOOCs for ongoing education and skillbuilding, the report found, demonstrating the potential of these courses for helping people gain real world skills. Data scientist took the no. 1 spot in Glassdoor's Best Jobs in America list in 2016 and 2017, and reports a median base salary of $110,000.

I've nearly finished the Coursera John Hopkins course on data science with R. It was pretty decent, some sections were definitely better than others. I know want to move on to a python data science course. I have used both Python and R for data science extensively, though I have probably used R more. I've been using Python for a couple years now along with many of the data analysis libraries such as Numpy, Pandas, Matplotlib, seaborn and their R equivalents. I was wondering if anyone knew what the best python data science course is?

This paper introduces the QMDP-net, a neural network architecture for planning under partial observability. The QMDP-net combines the strengths of model-free learning and model-based planning. It is a recurrent policy network, but it represents a policy for a parameterized set of tasks by connecting a model with a planning algorithm that solves the model, thus embedding the solution structure of planning in a network learning architecture. The QMDP-net is fully differentiable and allows for end-to-end training. We train a QMDP-net on different tasks so that it can generalize to new ones in the parameterized task set and "transfer" to other similar tasks beyond the set. In preliminary experiments, QMDP-net showed strong performance on several robotic tasks in simulation. Interestingly, while QMDP-net encodes the QMDP algorithm, it sometimes outperforms the QMDP algorithm in the experiments, as a result of end-to-end learning.

If you imagine the life of a machine learning researcher, you might think it's quite glamorous. You'll program self-driving cars, work for the biggest names in tech, and your software could even lead to the downfall of humanity. But, as a new survey of data scientists and machine learners shows, those expectations need adjusting, because the biggest challenge in these professions is something quite mundane: cleaning dirty data. This comes from a survey conducted by data science community Kaggle (which was acquired by Google earlier this year). Some 16,700 of the site's 1.3 million members responded to the questionnaire, and when asked about the biggest barriers faced at work, the most common answer was "dirty data," followed by a lack of talent in the field.

Three Dartmouth College professors whose research included studies on sexual attractiveness and desire have been placed on paid leave as a criminal investigation into sexual misconduct takes place. The Hanover, N.H., Ivy League school is the latest string of sexual misconduct allegations taking place in professional settings ranging from Hollywood to Washington D.C. New Hampshire Public Radio reports they've been put on paid leave and their access to campus is currently restricted. New Hampshire Attorney General Gordon J. MacDonald said his office is working with five law enforcement agencies as part of the joint criminal investigation into the alleged "serious misconduct" on campus, the college's student paper, The Dartmouth, first reported. The professors are all male, tenured faculty members. A 2012 research paper from Dr. Heatherton and Dr. Kelley studied how images of food and sex affect the brain.

Regardless of where you stand on the matter of Data Science sexiness, it's simply impossible to ignore the continuing importance of data, and our ability to analyze, organize, and contextualize it. Drawing on their vast stores of employment data and employee feedback, Glassdoor ranked Data Scientist #1 in their 25 Best Jobs in America list. So the role is here to stay, but unquestionably, the specifics of what a Data Scientist does will evolve. With technologies like Machine Learning becoming ever-more common place, and emerging fields like Deep Learning gaining significant traction amongst researchers and engineers -- and the companies that hire them -- Data Scientists continue to ride the crest of an incredible wave of innovation and technological progress. While having a strong coding ability is important, data science isn't all about software engineering (in fact, have a good familiarity with Python and you're good to go).