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Importance of Machine Learning and Data Science in the Fashion Industry

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machine learning and data science in the fashion industry

Importance of data science in fashion

While the sharp use of data science projects also known as data analytics projects is at the focus of every business and trade, it is even more powerful when applied to the fashion sector. Apparel brands need to manufacture, develop and sell styles that match the customer’s needs. AI software is used to develop marketing strategies, merchandising, and fashion designs.

According to forecasts of McKinsey Global Fashion Index (2018) adoption of advanced analytics, mobile internet, robotics, and advanced robotics are profoundly setting the stage for impactful trends towards an ultimate phase of digital acquisition by conventional consumers. A study conducted by JDA Software in 2018 found that over 40 percent of retailers highlighted the importance of data science in fashion brands and preferred customer-based data-driven science investment to convert data into customized products as per their localized trends and lifestyle. It is also used in the mechanical industry for a vision system inspection.

Factors to be considered while implementing data science in fashion

The biggest change that occurred in the usage of big data in the fashion business is that cognitive computing is implied to mimic brain functions and to stimulate human thought processes to discover customer needs. They improvise the operations and design of management stores and shops using data analytics.

It is also vital to understand that the application of artificial intelligence in the couture zone is tricky since different territories have different names for different garments. For instance: Pants in the US are trousers in the UK. To address these issues, algorithms, structured photographic brands, data, and natural language processors are designed using a counterintuitive approach to help customers choose their kind of clothing online. This is important to avoid too many returns because of poor fits.

Data science tools to be used by fashion industries

A machine learning platform is offered by DataRobot for data scientists to deploy and build accurate predictive models within a fraction of time. On the other hand, Qubole allows easy access to data-driven insights for the customers.

These intelligent tools, when used by couture companies will extract the best attributes, pointing out the unpopular ones. Brands can expect huge acceptance of different styles in the market and increased inventory turns by such iterative assortment planning.

Case Study on the emergence of AI in the fashion and retail sector

Amazon entered the market with its latest technological advancements using big data, machine learning, and AI as a game-changer. This way, Amazon was way ahead of all other retail brands. We know it for its’ Echo Look device’ based on data analytics that was used to buy real-time fashion insights. The dramatic influence of Amazon and its latest technological advancement drove the apparel industry to bring in changes and upgrade its technologies.

Echo Look by Amazon:

Amazon Echo Look is a style and camera virtual assistant for customers. Voice recognition capabilities are used to offer fashion advice, take photos and videos. The artificial intelligence of Amazon powers logic for the ‘Echo Look ChatOps’ interface is used to direct the device with commands that relay information. Responses are further generated using speech recognition technology by processing commands. For instance: Outfit photos can be stored by a user on a Lookbook (personal album). The’ Echo Look’ also processes weather updates, Alexa skills, and Smart Home- controls.

How can you be a data scientist for the fashion sector?

Current graduates or postgraduates aspiring to work in the apparel traffic can opt for data-driven science certifications by the Data Science Council of America (DASCA). Associate Big Data Analyst (ABDA) is one of the important big data analytics credentials for individuals graduating in marketing, business management, and related specializations. Individuals working in the fashion marketing area seeking faster growth in market research and data analytics can opt for Senior Big Data Analyst (SBDA) credentials.

To summarize:

Big data is a massive development for both consumers and the apparel makers that are eager for improvisations. Now that data science is used in the world of fashion it helps the retailers and manufacturers to keep up with the customer demands and latest trends. Data-powered decisions will give the fashion industry a competitive edge.