Here we discuss general applications of statistical models, whether they arise from data science, operations research, engineering, machine learning or statistics. We do not discuss specific algorithms such as decision trees, logistic regression, Bayesian modeling, Markov models, data reduction or feature selection. Instead, I discuss frameworks - each one using its own types of techniques and algorithms - to solve real life problems. Most of the entries below are found in Wikipedia, and I have used a few definitions or extracts from the relevant Wikipedia articles, in addition to personal contributions. Spatial dependency is the co-variation of properties within geographic space: characteristics at proximal locations appear to be correlated, either positively or negatively. Methods for time series analyses may be divided into two classes: frequency-domain methods and time-domain methods.

The deep penetration of internet among users in India has paved way for digitization. Digital platforms are leveraging new age technologies such as AI to make lives easier and enriching. Parenting too has joined the digital/ AI bandwagon. Today there are several apps that have implemented AI to help parents nurture and groom their children. This was a much needed revolution in assisting parents to understand the needs and psychology of their children. It guides them throughout the parental journey and helps in develop a mutual understanding that results in healthy relationships within the family.

Artificial intelligence has played a role in customer service for some time now, but it's only recently that its full potential for transforming the customer experience has come to light. Conversational commerce is redefining the role of messaging apps in customer engagement, while self-service tools continue to simplify the customer service process and shift the role of human customer service agents in the contact center. Here are six ways artificial intelligence is reshaping customer experiences of both the present and the future. Targeted marketing practices based on customer behavior. Big data is a key player in targeted marketing practices, offering brands important insights into customer behavior.

What are the most common patterns found in passwords? Based on these patterns, how to build robust yet easy-to-remember passwords? Does this password data set look OK, or do you think it is somewhat inaccurate or not representative of the password universe? If not, can we still draw valid conclusions from this data set, and how? What are the most common patterns found in passwords?

Fashion portal Myntra, part of India's top e-commerce group Flipkart, aims to use smart technology such as artificial intelligence to enhance consumer experience as it looks to drive growth and turn profitable in the next fiscal year. India's e-commerce market is forecast to grow to $188 billion (roughly Rs. 12,85,042 crores) in a decade as more and more of its 1.2 billion people log on to smartphones and PCs in the world's fastest-growing Internet services market. Players such as Flipkart and Myntra took a page out of Amazon's playbook to offer cash-burning discounts when they launched in 2007 but are now increasingly tailoring their products and experiences to capture a burgeoning Indian market.

This is a guest post written by Scott Middleton, founder and CEO of stratejos as well as part-time sausage maker. Will you still be doing your job in 5-10 years or will a robot do it for you? This is a question knowledge workers have started asking themselves as AI is becoming more capable and widely adopted. Atlassian co-founder and CEO, Mike Cannon-Brookes, has said AI will play a major role in the future of team productivity. Bank of America Merrill Lynch predicts that AI will have a $9 trillion impact on knowledge work over the coming decade.

Opinions expressed by Forbes Contributors are their own. The author is a Forbes contributor. The opinions expressed are those of the writer.

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This is a YouTube link to a PBS (Nova) documentary on IBM Watson: The smartest machine ever build - The first time I watched this, I thought'hey something is wrong here'. I went back and watched it again. I got another person to watch and validate - there were no women scientists, and there are hardly any women speaking in this documentary. Recently I read this article written a few months back with the title - Artificial Intelligence Has a'Sea of Dudes' Problem. The number of women in computing is low and it looks like the number of women in Machine Learning and Artificial Intelligence is even lower.

Groups of data scientists and regular users will be able to collaboratively prepare and share their data for analysis with the latest release of Birst's analytics platform. Version 6 of the company's suite also adds more automated smarts through tactical applications of machine learning, and extends the company's advancements in lineage tracking. Birst develops a well-regarded SQL-based analytics application that was developed from the beginning to run on multi-tenant cloud architectures. The software, which can be used on-premise or as a SaaS offering, stores data in column-oriented databases, such as Amazon Redshift, SAP HANA, or Exasol, while users interact with the data and create visualizations using Web and mobile interfaces. As a full-stack data analytics vendor, one of the analytic tasks that Birst tackles is data prep.