There's no denying that Google Home and Amazon Echo (or the less-expensive Echo Dot, if you're not using it for music) have changed the way we interact with our homes. Turning on the lights has never been easier, nor has it been simpler to field the latest traffic report or order delivery for dinner. The future is here, and we're reveling in it! But the proliferation of these devices around our homes leaves room for error. Google's and Amazon's connected speakers must always listen for us to utter their magic "wake" words--OK Google or Alexa respectively--in order to perform their tasks.

Whilst the use of machine learning in marketing seems to be skyrocketing, there's a dearth of coverage in the media that tries to get to the bottom of this technology in terms a layman can understand. I am irrefutably a layman, and have written a little on the topic of AI for Econsultancy, often specifically about ecommerce. In this blog post, we'll be talking to the founder of LoveTheSales.com, Before we start, let me point out that this year's Festival of Marketing has a whole stage (one of 12) dedicated to AI. View the agenda and get your tickets here. Machine learning is used to classify these products, tagging them to enable the website to sort them into the right categories and to show a user products they may be interested in.

What lies at the heart of this book is a great story of a relationship between man and machine, changing as D acquires human-like intelligence – and a human-like body - which provides the framework for an exploration of artificial intelligence and the potential for AI's self-development, where the future of AI may lead, and how we might interact with these bots as they form personalities of their own. Skillfully written with a fast-paced story, it's a fascinating read that has kept me thinking since I finished reading it.

Launching a webstore in 2017 has become easy. Despite that, growing and scaling an online business remains extremely difficult even for the most seasoned brands and eCommerce experts. Ecommerce sales are growing, often at the expense of retail store foot traffic, but many retailers are struggling to capitalize on their digital sales channels. The secret to success is no longer just to get it out there and see how it performs. The most successful retailers are strategic and targeted in their efforts, both offline and online, incorporating sales strategies as well as data to gather a deeper understanding of their customers.

This is a real mega-work on advanced topics and implementations in Python. My only reservation is one I have about all his books, that language gets very contorted and unclear in the middle of things that need elucidation. Sometimes I'm unsure I've read something more than gibberish. Often he could explain things in a far simpler way. His drive to appease different computer-language religions and Python versions generates a lot of clutter in the learning process.

First some general, higher-level thoughts and comments before I dive into specifics: MY BACKGROUND: Data Scientist; B.S. in Economics and M.S. in Business Analytics; experienced (though by no means expert) user of Scikit-learn OVERALL THOUGHTS: I've purchased and read (virtually) every Machine Learning book that aims to teach the reader the basics of ML using the Scikit-learn library as the main focus. I've found them to be...less than satisfactory. The examples in other books often use ML techniques in contexts for which they are not intended to be used and/or contexts they are not used in out in the real world (among other issues I have found within them). In stark contrast, Python Machine Learning by Sebastian Raschka is stunningly-impressive, not only for the breadth and depth of coverage, but also in the manner the information is presented to the reader. To date, I have not encountered a book on ML that incorporates multiple levels of learning in a manner such as this.

Data mining is not an intuitive activity. It requires skills and techniques which can be honed by using books like data mining: practical machine learning tools and techniques. This book is an ultimate guide for applying machine learning techniques and tools in real-world situations of data mining. The book will help you interpret outputs, evaluate results and prepare inputs and will provide the algorithmic methods for efficient data mining. You will not only find the explanation of concepts in this book but will also come across practical advice for successful data mining.

Advances in artificial intelligence are destined to make our lives and shopping experiences even better – good news for the consumer, and good news for retailers – but will machines eventually out-do humans, asks Uwe Hennig, chief executive of retail tech specialist Detego? There have been a number of buzzwords and defining technology trends in retail over the last decade: from Big Data, to Omni-channel, and the ubiquitous, omni-present Cloud. And now the internet of things (IoT) and artificial intelligence (AI) have seemingly become the latest crazes and talk of the town. Forrester expects investment in AI to triple this year. By 2020, 85 percent of customer interactions will be managed by AI according to research by Gartner.

Amazon is currently holding a multi-city job fair where it is expected to hire more than 50,000 people for retail jobs. But, in what seems to be a paradox, the company is also steadily employing robots at its plants and is developing technology which would one day take over these jobs, and replace humans at its warehouses. The company, which has given retail giants such as Walmart and Kroger a run for their money is the fourth largest retail employer in the U.S. Walmart leads in terms of jobs, with 2.3 million employees on its rolls, Kroger comes in second with 443,000 employees and Home Depot is on third place with 406,000 staffers. Amazon currently employs 341,000 employees, but is looking to hire more, which could soon push it to number three. Read: Walmart Plans To Create 1.5 Million Jobs, Unveils Manufacturing Strategy The company is also offering good incentives -- a minimum wage of $14 along with health insurance, retirement savings plan and stock awards, which is why thousands of people are queuing up for positions at its fulfillment centers.

Retailers are increasingly leveraging artificial intelligence technology, and 87 out of 100 retailers using AI are doing so to increase customer engagement, according to a study from customer care automation platform company Linc and branding firm BrandGarage. The study indicated that a vast majority of those surveyed plan to embrace AI specifically in the next 24 months, and will be on the hunt for AI-powered solutions that improve customer service. Additionally, the study stated that 34% of those surveyed have begun experimenting with customer-facing AI trials or pilots, though it also noted that only 7.7% of retailers have rolled out AI as a regular part of customer service to-date. On the surface, there is nothing too surprising about these survey results, though hearing about 87% of a group of retailers all whistling the same tune about anything is enough to make one sit up and take notice. AI has slowly been creeping into retail operations, both in customer-facing and back office applications, and this survey suggests that any organizations who weren't on board with that notion before are embracing the technology.