In this paper, we report an industry-academia collaborative study on the distribution method of fashion products using an artificial intelligence (AI) technique combined with an optimization method. To meet the current fashion trend of short product lifetimes and an increasing variety of styles, the company produces limited volumes of a large variety of styles. However, due to the limited volume of each style, some styles may not be distributed to some off-line stores. As a result, this high-variety, low-volume strategy presents another challenge to distribution managers. We collaborated with KOLON F/C, one of the largest fashion business units in South Korea, to develop models and an algorithm to optimally distribute the products to the stores based on the visual images of the products. The team developed a deep learning model that effectively represents the styles of clothes based on their visual image. Moreover, the team created an optimization model that effectively determines the product mix for each store based on the image representation of clothes. In the past, computers were only considered to be useful for conducting logical calculations, and visual perception and cognition were considered to be difficult computational tasks. The proposed approach is significant in that it uses both AI (perception and cognition) and mathematical optimization (logical calculation) to address a practical supply chain problem, which is why the study was called "Breaking Moravec's Paradox."

In this paper, we describe a novel solution to compute optimal warehouse allocations for fashion inventory. Procured inventory must be optimally allocated to warehouses in proportion to the regional demand around the warehouse. This will ensure that demand is fulfilled by the nearest warehouse thereby minimizing the delivery logistics cost and delivery times. These are key metrics to drive profitability and customer experience respectively. Warehouses have capacity constraints and allocations must minimize inter warehouse redistribution cost of the inventory. This leads to maximum Regional Utilization (RU). We use machine learning and optimization methods to build an efficient solution to this warehouse allocation problem. We use machine learning models to estimate the geographical split of the demand for every product. We use Integer Programming methods to compute the optimal feasible warehouse allocations considering the capacity constraints. We conduct a back-testing by using this solution and validate the efficiency of this model by demonstrating a significant uptick in two key metrics Regional Utilization (RU) and Percentage Two-day-delivery (2DD). We use this process to intelligently create purchase orders with warehouse assignments for Myntra, a leading online fashion retailer.

Amazon's Summer Sale has just passed the halfway mark, and there are still thousands of discounts to be had on tech, beauty and home products until 11.59 pm on July 12, with new items dropping each day. As we expected, some of the most popular deals have included up to 50 per cent off Amazon's Echo smart speaker and reduced prices on other top tech from the likes of Garmin and Shark. However, we recommend signing up to Amazon's Prime subscription service now with a 30-day free trial to receive free next-day delivery and access to some exclusive offers. There are still many offers worth checking out, and if you're curious to know what everyone else has snapped up during Amazon's Summer Sale, you can check out the top-selling and best deals so far below. Here's what MailOnline readers are buying: Amazon has slashed the price of this all-singing-all-dancing Garmin Vivoactive 3 GPS Smartwatch, now 53 per cent off in the Summer Sale.

"Can artificial intelligence actually help connect with customers, let alone engage them?" Nod, if you too have wondered about this at one point or another. The answer is deceptively simple: AI has direct and indirect applications, both of which ultimately benefit the end-customer. AI is no longer a nice-to-have business advantage. It has emerged as a must-have and how.

As we progress from "the new normal" to "the next normal," businesses are working hard to revise their marketing strategy and develop an omnichannel presence to improve sales in the brave new world of e-commerce. Read on to learn everything you ever wanted to know (and then some) about omnichannel, including what it is, how to build yours with voice commerce, and how to use it to maximize reach and fulfill consumer needs. Recently, Forrester hosted the Engage Digital conference, a virtual adaptation of its annual user event. According to Brendan Witcher, Principal Analyst for Digital Business Strategy, "the next normal" will "involve advances in omnichannel." During his presentation, Witcher noted that it will be necessary for retailers to switch gears to be prepared for the next phase of e-commerce.

As a data scientist attempting to solve a problem using supervised learning, you usually need a high-quality labeled dataset before starting your model building. Amazon SageMaker Ground Truth makes dataset building for a different range of tasks, like text classification and object detection, easier and more accessible to everyone. Ground Truth also helps you build datasets for custom user-defined tasks that let you annotate anything. For complex labeling tasks, such as complex taxonomy classification, extreme multi-class classifications, or autonomous driving labeling tasks, you may need to build a more complex front-end application for your labeling workforce. Front-end frameworks like Angular are helpful in these cases because they bring useful design patterns like model-view-controller (MVC), which makes your codebase more robust and maintainable for a larger team composed of UX/UI designers and software developers.

Those who want to outfit a room or two with smart displays can get a couple of Amazon's smaller Echo Shows for less at HSN. The online retailer has a bundle that includes one Echo Show 5 and one Echo Show 8 for $140, which is a great price and close to the sale prices we saw for both of those devices back in May. If you were to buy each smart speaker separately right now, you'd spend $170 -- and that's with both the Show 5 and the Show 8 technically being on sale. In May, Amazon dropped the prices of both smart speakers to their Black Friday lows. If you had purchased one of each then, you would have paid $130.

Forecasting is a technique that uses historical data and events to build estimates about future trends, potential disasters, and the overall behavior of any subject. Forecasting can be used as probabilistic support for decision analysis, to estimate expenses, revenues, and budget plans. Forecasting in business can be divided into two distinct categories: qualitative forecasting and quantitative forecasting. For more information, you can take a look at Investopedia's Financial Forecasting primer. Both types of forecasting have shown a lot of promise and managed to create business enhancements for many entities.

With the increasing use of machine learning technology, the retail sector is having a significant impact, they can now boost efficiency and productivity while actively engaging consumers through digital and mobile devices. McKinsey's latest study found that "U.S. retailer supply chain operations that have adopted data and analytics have seen up to a 19 percent rise in profit margin over the last five years". Machine learning comes as a boon for retailers to anticipate customer behavior with a greater degree of accuracy by understanding what products their shoppers are interested in, rather than making intuitive guesses or exhaustive analyses to optimize operations.

Simon Rogers is a lecturer in the School of Computing Science at the University of Glasgow, where he teaches a masters-level machine learning course on which this book is based. Dr. Rogers is an active researcher in machine learning, particularly applied to problems in computational biology. His research interests include the analysis of metabolomic data and the application of probabilistic machine learning techniques in the field of human-computer interaction. Mark Girolami holds an honorary professorship in Computer Science at the University of Warwick, is an EPSRC Established Career Fellow (2012 - 2017) and previously an EPSRC Advanced Research Fellow (2007 - 2012).