With strong roots in statistics(data), Machine Learning is becoming among the very fascinating and quick-paced computer science areas to work in. There is an unending source of businesses and software machine learning could be implemented to make them more wise and skillful. Chatbots, spam filtering, advertising serving, search engines, and fraud detection, are one of just a few examples of machine learning versions encourage everyday day to day life. Machine Learning is what allows us find patterns and create mathematical models for matters that would at times be unthinkable for individuals to perform. Not at all like informatics courses which include topics such as methods of exploratory data analysis, data, communication, and visualization, machine learning courses only focus on teaching machine learning algorithms the way they are numerically A programming language, and how to use them.

This will make this area of data science even more commonplace not only among top tech companies, but also small and medium-sized businesses across various verticals. However, one aspect which is potentially underrated when looking at the big trends, in terms of the future of data science, is around language frameworks used to make the everyday data science tasks possible. Today, there are two major frameworks, R or Python (or in more pragmatic data science circles, both!). One is praised for having the most beautifully designed data wrangling syntax and plotting libraries, the other for its expressiveness and having the best deep learning libraries available today. However, both suffer from being relatively slow as they're higher level languages.

Everyone knows the saying: "A picture is worth a thousand words." In today's world of social posting, it's never been truer. But how do you predict which of those "thousand words" are truly relevant to your customer? To drive high conversion ratios, predictive marketing needs to target precisely relevant offers to attract and engage each customer individually. As marketers, we typically use experimentation, A/B testing or focus groups to assess relevance.

Predictive analytics in marketing, as I mentioned in my last post, is here. Already, this all-encompassing disruption in the fundamentals of marketing and sales is changing how marketing specialists and bloggers are talking about their industry. Machines can predict what you want, when you will want it. Pretty intense stuff, right?! Suddenly the larger than life 3D pink hologram woman from Blade Runner 2049 that bends down to talk specifically to you doesn't seem so far fetched, huh? If you've missed the movie, Blade Runner 2049, go see it, it's good, (although I'm still most partial to the 1982 original Blade Runner).

"Hey, Siri! Find the nearest sushi restaurant." New technologies are emerging and showing up in our everyday lives at a rapid rate. Voice-recognition, like Apple's Siri or Amazon's Alexa, and image recognition in our Facebook and Google accounts are just two mainstream applications that leverage artificial intelligence (AI)--one of the newest technologies gaining widespread momentum today. Artificial intelligence (AI) is defined by the Association for the Advancement of Artificial Intelligence as "the scientific understanding of the mechanism underlying thought and intelligent behavior and their embodiment in machines." It is one of the Top 10 Emerging Technologies of 2016 chosen by the World Economic Forum, based on the power to improve lives, transform industries, and safeguard the planet.

Before breakfast, I check my Facebook and LinkedIn newsfeeds for a quick synopsis of the day. As I jump in the shower, I hit "download" on a recommended movie on Netflix, knowing I have a long flight this evening. While wolfing down my cereal, I click once to buy a gift for a friend's birthday next week. My iPhone pings to tell me that I need to leave now if I want to make that early meeting 54 miles away. And as I get in my car, I use voice activation to play my favorite Spotify playlist, and Apple Maps informs me it will take five minutes to drive to the train station this morning.

It is pretty evident that AI and predictive marketing is rapidly changing the landscape of marketing. Marketing has been around for ages and predictive marketing is the newest innovation in this space. We have a lot of case studies that argues the same for AI's capabilities. It has helped us understand that there exists a gap between our marketing strategies. Now with the help of AI, we exactly know what has to be done and we have been arming our sales team with what they need to close deals.

Information contained on this page is provided by an independent third-party content provider. If you are affiliated with this page and would like it removed please contact pressreleases@franklyinc.com Joint customer Insight implements Mintigo's Predictive Analytics and Artificial Intelligence to deliver actionable sales intelligence into SAP C4C CRM Mintigo, the leader of predictive marketing and sales technology, today announced its new solution for infusing actionable sales intelligence into SAP's C4C. Mintigo's innovation is relevant to a potential demographic of businesses, who have never before been able to harness the true potential of predictive marketing for sales to increase their revenue. This unique integration, will allow SAP C4C and SAP Hybris Marketing users, such as Insight, to empower their sales organization with intelligent client profile information that facilitates more meaningful conversations with prospects and customers. Historically, enterprises using SAP have had a difficult time integrating relevant client information provided by machine learning tools.

Thank you for subscribing to the monthly THINK Marketing newsletter. Many business-people like you and me probably think of "marketing" as a set of processes that promotes our products and services with a view toward generating revenue and margin. Most consumers (also like you and me, when off-duty) probably think of "marketing" as a blur of information spamming our inboxes, mobile phones and brains. It's an altogether more negative connotation of a concept as ancient as "Adam, can I tempt you with an apple?" With "predictive marketing," businesses can better convert this negative experience into a positive perception of their brands, products and services. Put simply, predictive marketing uses advanced analytics methodologies to understand a customer's past behavioral profile, specifically the unique drivers of the individual's behavior, to predict their future behavior.

According to Forrester Tech Radar for B2B Marketing Technology and SD'16 (SiriusDecisions conference 2016), two of the hottest trends last year were ABM (Account-Based Marketing) and Predictive Marketing. I'm sure you all are now busy with deploying your ABM initiatives. Many of you have embraced or thinking of Predictive Marketing. AI is the red hot topic that is being discussed at c-level in all organizations. We all are beneficiaries of AI in our daily lives; from Alexa and Siri to TacoBot, we are reaping the rewards of AI.