Just to let you know, if you buy something featured here, Mashable might earn an affiliate commission. It's time to give that ol' brain of yours a thorough dusting-off, so to speak: Through the Full Neuro-Linguistic Programming (NLP) Diploma Course, you might be able to hack your way to an improved way of thinking. NLP, in case you haven't heard, is a set of rules and techniques designed to help you shape your personal psychology and achieve self-actualization. Some see it as pseudo-science, while others swear by it. Either way, the idea is that you can train your brain to eliminate phobias, tweak bad habits, and even gain a deeper understanding of others' body language -- skills that are beneficial in the workplace, your social life, and beyond.
I would recommend that you start with Introduction to Statistical Learning with R (usually shortened as ISLR). A lot of people have adapted the examples to Python if you google a bit and it's an excellent book that hides just enough complexity to not be overwhelming. Plus, once you have a good understanding of all of it, you can either graduate to the more extensive version (Elements of Statistical Learning, usually shortened as ESL) for a more rigorous treatment of the same thing, or choose to go for something different like Bishop's Pattern Recognition and Machine Learning. ISLR is free as a pdf and has a corresponding MOOC. ESL doesn't, but is also free on the author's website.
In the field of machine learning, online learning refers to the collection of machine learning methods that learn from a sequence of data provided over time. In online learning, models update continuously as each data point arrives. You often hear online learning described as analyzing "data in motion," because it treats data as a running stream and it learns as the stream flows. Classical offline learning (batch learning) treats data as a static pool, assuming that all data is available at the time of training. Given a dataset, offline learning produces only one final model, with all the data considered simultaneously.
For Peter Cao, who has dedicated 16 years of his career to teaching chemistry in a high school in central China's Anhui province, in every teacher there lives a "doctor". He spends two to three hours a day grading assignments, a process the 38-year-old describes as "diagnosing". "By reviewing the homework of my pupils, I can have an overall picture about their understanding of the lessons I give," Cao said, adding that this "diagnosis" helps him draw up a teaching plan for the following day. But if the Chinese online education start-up Master Learner has its way, Cao and his 14 million fellow teachers in China will be able to hand this time-consuming review process to a "super teacher", a powerful "brain" capable of answering nearly 500 million of the most tested questions in China's middle schools as well as scoring high points in each Gaokao test, China's life-changing college entrance exam, for the past 30 years. If the super teacher sounds too smart to be human, that is because it is not.
The history of Artificial Intelligence isn't a long one, around 60-70 years, but the advances in recent years has been huge. The Modern Artificial Intelligence Infographic shows how technology coupled with studies of the human brain have aided in making AI a reality, and a reality we can use everyday. Machines are already intelligent, but we fail to recognise it. When a machine demonstrates intelligence we counter it by saying'it's not real intelligence'. Therefore Al becomes whatever has not been accomplished so far by a machine.
If you have access to AI experts like professors, PhD students, or good researchers, talk to them too. Sometimes I've learned a ton from a 5 minute conversation with people like Geoff Hinton, Yoshua Bengio, Yann LeCun; but also from my PhD students at Stanford, team members at deeplearning.ai, Despite the importance of having friends to work with, if your friends disagree with your ideas, sometimes you should still implement it and try it out to see for yourself. If you have access to AI experts like professors, PhD students, or good researchers, talk to them too. Sometimes I've learned a ton from a 5 minute conversation with people like Geoff Hinton, Yoshua Bengio, Yann LeCun; but also from my PhD students at Stanford, team members at deeplearning.ai, Despite the importance of having friends to work with, if your friends disagree with your ideas, sometimes you should still implement it and try it out to see for yourself.
Though traditional personality-assessment techniques, such as the Myers–Briggs test, are designed for objectivity, somewhere along the way "managers still inject personal bias," says Mark Newman, founder and CEO of HireVue, a recruiting-technology company. Koru, another human resources software developer, also gauges personal attributes, using a written test to evaluate "impact skills," such as grit, curiosity, and polish. The year-old company Interviewed, which has worked with clients such as Instacart and IBM, administers "blind auditions" in which applicants for customer-service jobs field chats or calls from bots that represent consumers. An algorithm's ability to understand something like empathy, Bakke says, points to a new hiring technique--one in which machines assess, but humans make the final call.
The Data Mining Specialization teaches data mining techniques for both structured data which conform to a clearly defined schema, and unstructured data which exist in the form of natural language text. Specific course topics include pattern discovery, clustering, text retrieval, text mining and analytics, and data visualization. The Capstone project task is to solve real-world data mining challenges using a restaurant review data set from Yelp. You can apply to the degree program either before or after you begin the Specialization.
Serengil received his MSc in Computer Science from Galatasaray University in 2011. Currently, he is a member of AI and Machine Learning team as a Data Scientist. His current research interests are Machine Learning and Cryptography. Nowadays, he enjoys speaking to communities about these disciplines, also blogging and creating online courses related to his research interests.
Mike Salem from Udacity's Robotics Nanodegree is hosting a series of interviews with professional roboticists as part of their free online material. This week we're featuring Mike's interview with Felipe Chavez, Co-Founder and CEO of Kiwi. Kiwi is a mobile robot company delivering food to hungry college students across University of California, Berkeley's campus. Listen to Felipe explain some of the challenges Kiwi faces when deploying their robots.