Lately, there has been a lot of buzz about Chatbots – applications that make use of a conversational user interface instead of a graphical interface that has been the norm in the past decade or three. With any buzz-worthy technology, there is the usual confusion about what exactly is a Chatbot – and depending on how many articles you have read, it is anywhere between a simplified IVR or the technology which will result in world peace. Neither Chatbots nor Conversational User Interfaces are new. All businesses must think whether they need to have a strategy to have a "Conversational App" – just like they all had to for mobile apps. Bot-directories on the Internet are already full of shallow and meaningless Chatbots, just like app stores were when mobile apps became all the rage.

When it comes to enterprise customer care, machine learning enables virtual assistant solutions to automate tasks that used to require a live agent: password resets, address and complex information collection, even sales support. Integrating machine learning into enterprise customer care opens doors to more flexible automated solutions. It also frees up live agents to focus on handling complex or revenue-generating tasks. With the growing challenges and volume of customer interactions that most companies must handle, that flexibility, efficiency, and accuracy is exactly what's needed. With a little help and vetting from the IT department, the contact center can take enterprise customer care to the next level. Of course, success comes with a cost.

We can see a few interesting things in this table. In a similar talk by Owen at ODSC Boston 2015 titled "Open Source Tools and Data Science Competitions", he again summarized common parameters he uses: We can see some minor differences that may be relevant. Finally, Abhishek Thakur, in his post titled "Approaching (Almost) Any Machine Learning Problem" provided a similar table listing out key XGBoost parameters and suggestions for tuning. The spreads do cover the general defaults suggested above and more. It is interesting to note that Abhishek does provides some suggestions for tuning the alpha and beta model penalization terms as well as row sampling. You can develop and evaluate XGBoost models in just a few lines of Python code.

Xperilabs is a machine learning, data science and algorithms studio for Indian Financial Markets. We are currently working in stealth mode, rapidly developing the pre-beta version of our platform. Our vision is to build a state-of-the-art platform that offers tools and algorithms that will allow retail as well as institutional investors to explore and design quantitatively driven financial algorithms.

The short answer: To make their lives easier. Marketers have depended on tools and technology to automate their work and reduce manual effort for a while. Yet, there has always been a gap in terms of effort and quantifiable results. Intuition on the right audience and time to send messages aren't enough to answer a digital marketer's basic questions. Who should I reach out to? What should I send?

Spending thousands of hours playing Grand Theft Auto might have questionable benefits for humans, but it could help make computers significantly more intelligent. Several research groups are now using the hugely popular game, which features fast cars and various nefarious activities, to train algorithms that might enable a self-driving car to navigate a real road. But the stunningly realistic scenery found in Grand Theft Auto and other virtual worlds could help a machine perceive elements of the real world correctly. A technique known as machine learning is enabling computers to do impressive new things, like identifying faces and recognizing speech as well as a person can. But the approach requires huge quantities of curated data, and it can be challenging and time-consuming to gather enough.

Top e-retailers apply artificial intelligence, bots and a mobile-first approach to push mobile commerce well beyond sites and apps. Many retailers are likely familiar with, and perhaps even own, a Staples Easy Button. They may have even tapped the tchotchke a time or two, prompting the bright red plastic button to cheerfully chirp the office supply retailer's tagline, "That was easy!" But calling out the retailer's slogan was the extent of the Easy Button's capabilities. Staples is testing how consumers react to it incorporating machine learning in its Easy Button that enables shoppers to press the button to order a product by voice, or to ask common questions, such as when an order will be delivered or the status of a return.

Researchers at the University of Leuven in Belgium said a study they conducted showed artificial intelligence could help interpret, and thereby improve, lung function tests used to diagnose long-term lung disease. Results of the study were presented Monday at the European Respiratory Society's International Congress. As part of the study, the researchers used data from 968 people who were undergoing complete lung function testing for the first time. Using a concept called "machine learning", they developed an algorithm that takes into account routine lung function parameters and clinical variables of smoking history, body mass index, and age to make a suggestion for the most likely diagnosis. "We have demonstrated that artificial intelligence can provide us with a more accurate diagnosis in this new study," Wim Janssens, senior author of the study, said.

WASHINGTON – CIA Director John Brennan warned on Sunday that Russia has "exceptionally capable and sophisticated" computer capabilities and that the U.S. must be on guard. When asked in a television interview whether Russia is trying to manipulate the American presidential election, Brennan didn't say. But he noted that the FBI is investigating the hacking of Democratic National Committee emails, and he cited Moscow's aggressive intelligence collection and its focus on high-tech snooping. "I think that we have to be very, very wary of what the Russians might be trying to do in terms of collecting information in a cyber realm, as well as what they might want to do with it," he told CBS' "Face the Nation" on the 15th anniversary of the Sept. 11 attacks. On the terrorism threat, Brennan said the U.S. government is much better now at sharing information.

Turnkey software allows brands to manage their messaging presence across all of the most popular messaging apps from a single dashboard. Our analytics capture trending topics and conversation sentiment, and uncover new sales and engagement opportunities to propel messaging as a core channel for unprecedented user engagement, operational efficiency and sales.