A Deep Guide to Text-Guided Open-Vocabulary Segmentation
Discover the power of text-guided open-vocabulary segmentation using large language models like GPT-4 & ChatGPT for automating image and video processing tasks.
Shopify stores and marketplaces use product taxonomy trees to organize their products in their catalog to make it easier for customers to find what they’re looking for. The hierarchical structure allows ecommerce stores to refine and filter their categories into granular groups to help customers to reach products in the least amount of time and clicks.
Shopify Product Taxonomy (SPT) is an ecommerce taxonomy tree with 5,595 unique categories used by Shopify to categorize products in a customer's store into a standard tree. There are two ways to categorize products in Shopify, standardized and custom product types. Standardized product types use only a predefined product category from the Shopify Product Taxonomy (SPT). The SPT is an extension of the popular Google Product Taxonomy with small modifications to account for extra categories.
Custom product types allow you to input a custom category that is based on your own internal taxonomy tree or because the category doesn’t exist in the SPT. It’s best practice to only use a custom product type if you cannot find a category match for your product’s main function or the SPT category is not specific enough given the granularity of your store's products. A great example of this is the Google Product Taxonomy category “Apparel & Accessories > Shoes”. This is as deep as the tree goes and would not be granular enough for a shoe marketplace.
There are a number of reasons why it's beneficial to organize products with standardized product types in Shopify.
- A key reason for using the Shopify Product Taxonomy is the ease it provides when selling products on other channels such as Facebook and Google Shopping Feed. These product categories have an associated ID that is often required in these platforms for categorization and sales tax reasons.
- It makes it much easier to manage your product catalog and create an effective hierarchical structure for your store. A Forrester research study found that poorly structured sites sell 50% less than organized sites.
- Search engines favor the structure that Google Product Taxonomy provides when ranking product pages. The Shopify Product Taxonomy follows the same categories and is nearly identical.
- When using the direct checkout feature on Instagram or Facebook the Google product category ID number is required for tax reasons.
You can start manually adding a standardized product type to your products in Shopify by going to the Shopify admin and clicking a product. Then in the product organization section click Type. From there you can either enter your product’s type and select what you feel is the most accurate result from the standardized type list or click through each level of the taxonomy tree and find the deepest product category.
The steps for doing this from the mobile app are:
- Go to Products > All products
- Tap on a product to edit it
- Go to More details and then product organization
- In the “Type” Section you have two options - click on the magic wand to choose the suggested type for your product or click “Add type” to search for a specific category.
Deep learning & Ai has made it easy to automatically categorize Shopify products into the standardized Shopify Product Taxonomy in bulk. These models have learned the relationship between the SPT tree and product data with over 92% accuracy. This relationship uses deep learning with millions of examples so there’s no need for business transformation rules or keyword matching algorithms.
You can go from thousands of Shopify products to structured, categorized data in a matter of minutes with Pumice.ai.
The first step is gathering product data and preparing it for automatic categorization through our endpoints. Pumice.ai endpoints require the product title and description and have optional fields of price and GTIN. Shopify allows you to export your existing products via a CSV and reimport your products with your new categories (guide).
You can interact with the Pumice.ai endpoints through the dashboard or a direct connection to the APIs. In the dashboard, you’ll be required to upload your product data CSV file and will receive a CSV back with your product data and the categories. API connection allows you to add automatic categorization to your product creation workflow and remove any manual effort needed to process.
Both the Google Product Taxonomy and Shopify Product Taxony are built into our dynamic categorization endpoint and offered as fine-tuned models. These models have been trained on millions of products and use examples from popular ecommerce stores such as Amazon, Macy’s, Shopee, eBay, and more. Simply select the model_id for either Shopify or Google taxonomy and start categorizing products.
Once you’ve uploaded and mapped your product data, or connected to the API you’re good to go! You’ll receive your results back in the same format you sent them in. Our dynamic categorization API focuses on fitting product data to categories dynamically at runtime. This means the deep learning models do not need specific training on your product data or hierarchical taxonomy structure.
This endpoint can also be used for a “custom type” taxonomy in Shopify. Store owners can export their custom taxonomy instead and start classifying products. Unlike when using the standard taxonomy you’ll be required to upload a taxonomy file in the same format as the standard taxonomy.
Once you’ve run the dynamic categorization endpoint and generated product categories you can take advantage of this data by adding them to your online store products. This data can be automatically uploaded to Shopify through our custom integration available to enterprise customers. This takes your automation to the next level with zero human intervention to go from bulk uncategorized product data to live products.
Pumice.ai is a PIM enhancement platform that leverages ai models to help customers automate product information tasks. Our starter package allows you to get started with automation endpoints such as the Shopify product categorization endpoint in a matter of minutes with no custom models required. You can join today and stop wasting time on manual PIM: Let’s Go
Here’s a list of the categories as provided by Shopify.
Discover the power of text-guided open-vocabulary segmentation using large language models like GPT-4 & ChatGPT for automating image and video processing tasks.
Learn how CLIPSeg segmentation, in combination with GPT-4 and ChatGPT, can enable diverse applications from medical image diagnosis to remote sensing.
Can GPT-4 make your life as a finance or banking employee easier? Learn how GPT-4 and NLP can be used in finance to increase revenues and streamline workflows.
A deep dive into how we reached SOTA accuracy in product similarity matching through a custom fine-tuning pipeline that refines the CLIP model for image similarity.
Boost your conversions and sales numbers with NLP in sales using OpenAI's GPT-3 and GPT-4. You can use chatbots to improve customer experience and loyalty.
Explore the use of GPT for opinion summarization through innovative pipeline methods, evaluation metrics like ROUGE and BERTScore, and human evaluation insights. Dive into novel entailment-based evaluation tools for a comprehensive understanding of model performance in capturing diverse user opinions.
Come aboard the large language model revolution with our deep dive on AI21 vs. GPT-3 for business use cases like ad copy generation and math proof generation.
A technical guide to using BERT for extractive summarization on lectures that outperforms other NLP models
Discover how prompt based LLMs like GPT-3 & GPT-4 are transforming news summarization with its zero-shot capabilities and adaptability to specialized tasks like keyword-based summarization. Learn about the limitations of current evaluation metrics and the potential future directions in text summarization research.
Discover the PEZ method for learning hard prompts through optimization, a powerful technique that enhances generative models for image generation and language tasks, improves transferability, and enables few-shot learning
Take a look at how Width.ai built 17 generative ai pipelines for use in the Keap.com marketing copy generation product
A deep look at how recurrent feature reasoning outperforms other image inpainting methods for difficult use cases and popular datasets.
See a comparison of GPT-3 vs. GPT-J, a self-hosted, customizable, open-source transformer-based large language model you can use for your business workflows.
Discover how transformer networks are revolutionizing image and video segmentation, and get insights on modern semantic segmentation vs. instance segmentation.
Discover how the state-of-the-art mask-aware transformer produces visually stunning and semantically meaningful images and how it stacks up against Stable Diffusion & DALL-E for large-hole inpainting
Unlock the full potential of spaCy with this guide to building production-grade text classification pipelines for business data.
We compare 12 AI text summarization models through a series of tests to see how BART text summarization holds up against GPT-3, PEGASUS, and more.
Let’s take a look at what intent classification is in conversational ai and how you can build a GPT-3 intent classification model for conversational ai and chatbot pipelines.
Discover the capabilities of zero-shot object detection, which enables anyone to use a model out-of-the-box without any training and generate production-grade results.
What is facial expression recognition and what SOTA models are being used today in production
Get a simple TensorFlow facial recognition model up & running quickly with this tutorial aimed at using it in your personal spaces on smartphones & IoT devices.
Explore accurate classification algorithms using the latest innovations in deep learning, computer vision, and natural language processing.
Learn what human activity recognition means, how it works, and how it’s implemented in various industries using the latest advances in artificial intelligence.
What is the the SetFit architecture and how does it outperform GPT-3 and other few shot large language models
What is image classification and how we build production level TensorFlow image classification systems for recognizing various products on a retail shelf.
Explore the application of intelligent document processing (IDP) in different industries and dive in-depth on intelligent document pipelines.
How to build an image classification model in PyTorch with a real world use case. How you can perform product recognition with image classification
Let's build a custom CTA generator that you'll actually want to use for your website copy
We’re going to look at how we built a state of the art NLP pipeline for blended summarization and NER to process master service agreements (MDAs) that vary the outputs based on the input document and what is deemed important information.
Get a comprehensive overview of a purchase order vs. invoice, including when businesses use each, what information goes in them, and more.
Learn what Google Shopping categories are used for and how you can automate fitting products to this taxonomy using ai.
Dive deep into 3-way invoice matching, including how it works, eight benefits for your business, and the problems with doing it manually.
Smart farming using computer vision and deep learning provides the most promising path forward in the slow-moving industry of agriculture.
How we leveraged large language models to build a legal clause rewriting pipeline that generates stronger language and more clarity in legal clauses
Using ai for document information extraction to automate various parts of the loan process.
Apply AI to your favorite sport with this guide. Learn how automated ball tracking can change the game for coaches and players.
Categorize your ecommerce products to the 2021 google product taxonomy tree instantly with our Ai software
Surveying the current landscape of ecommerce automation and how you can use ai to automate huge chunks of your product management.
Classify your product data against an existing product category database or generate categories and tags in seconds using artificial intelligence
Warehouse automation plays a crucial role across your supply chain. Learn about how machine learning and ai software can be integrated into your warehouse automation stack.
4 different NLP methods of summarizing longer input text into different methods such as extractive, abstractive, and blended summarization
iscover an invoice OCR tool that will revolutionize the way you handle invoices. There’s no human intervention needed & a dramatically lower per-invoice cost.
Instead of invoice matching taking upwards of a week, it could take mere seconds with the proper automation solution. Learn more here.
Manual and template-based invoicing are riddled with low accuracy and required human intervention. Learn how to systematically eliminate these issues with the right invoice data capture software.
A complete walkthrough guide on how to use visual search in ecommerce stores to create more sales and real examples of companies already using it.
Automating the extraction of data from invoices can reduce the stress of your accountants by finding inaccuracies, digitizing paper invoices, and more.
How you can optimize email marketing campaigns with machine learning based models that improve conversion & click-through rates.
How you can use machine learning based data matching to compare data features in a scalable architecture for deduping, record merging, and operational efficiency
Learn how lifetime value or LTV prediction can improve your marketing strategies. Then, discover the best statistical & machine learning models for your predictions.
A deep understanding of how we use gpt-3 and other NLP processes to build flexible chatbot architectures that can handle negotiation, multiple conversation turns, and multiple sales tactics to increase conversions.
The popular HR company O.C. Tanner, which has been in business since 1927 and has over 1500 employees, was looking to research and design two GPT-3 software products to be used as internal tools with their clients. GPT-3 based products can be difficult to outline and design given the sheer lack of publicly available information around optimizing and improving these systems to a production level.
We’ll compare Tableau vs QlikView in terms of popularity, integrations, ease of use, performance, security, customization, and more.
With a context-aware recommender system, you can plan ways to recreate some of the contextual conditions that persuade them to buy more from you.
We’re going to walk through building a production level twitter sentiment analysis classifier using GPT-3 with the popular tweet dataset Sentiment140.
Find out how machine learning in medical imaging is transforming the healthcare world and making it more efficient with three use cases.
Discover ways that machine learning in health care informatics has become indispensable. Review the results of two case studies and consider two key challenges.
Accelerate your growth by pivoting key areas of your business to AI. Your business outcomes will be achieved quicker & you’ll see benefits you didn’t plan for.
We built a GPT-3 based software solution to automate raw data processing and data classification. Our model handles keyword extraction, named entity recognition, text classification | Case Study
We built a custom GPT-3 pipeline for key topic extraction for an asset management company that can be used across the financial domain | Case Study
How you can use GPT-3 to create higher order product categorization and product tagging from your ecommerce listings, and how you can create a powerful product taxonomy system with ai.
5 ways you can use product matching software in ecommerce to create real value that raises your sales metrics and improves your workflow operations.
Data mining and machine learning in cybersecurity enable businesses to ensure an acceptable level of data security 24/7 in highly dynamic IT environments. Learn how data security is getting increasingly automated.
Product recognition software has tremendous potential to improve your profits and slash your costs in your retail business. Find out just how useful it is.
Big data has evolved from hype to a crucial part of scaling your organization in every modern industry. Learn more about how big data is transforming organizations and providing business impacts.
Learn how natural language processing can benefit everybody involved in education from individual students and teachers to entire universities and mass testing agencies.
Here’s how automated data capture systems can benefit your business in some key ways and some real-life examples of what it looks like in practice.
Use these power ai and machine learning tools to create business intelligence in your marketing that pushes your business understanding and analytics past your competition.
We built a custom ML pipeline to automate information extraction and fine tuned it for the legal document domain.
In this practical guide, you'll get to know the principles, architectures, and technologies used for building a data lake implementation.
Find out how machine learning in biology is accelerating research and innovation in the areas of cancer treatment, medical devices, and more.
An enterprise data warehouse (EDW) is a repository of big data for an enterprise. It’s almost exclusive to business and houses a very specific type of data.
Dlib is a versatile and well-diffused facial recognition library, with perhaps an ideal balance of resource usage, accuracy and latency, suited for real-time face recognition in mobile app development. It's becoming a common and possibly even essential library in the facial recognition landscape, and, even in the face of more recent contenders, is a strong candidate for your computer vision and facial recognition or detection framework.
Learn how to utilize machine learning to get a higher customer retention rate with this step-by-step guide to a churn prediction model.
Machine learning algorithms are helping the oil and gas industry cut costs and improve efficiency. We'll show you how.
We’ll show you the difference between machine learning vs. data mining so you know how to implement them in your organization.
Here’s why you should use deep learning algorithms in your business, along with some real-world examples to help you see the potential.
Beam search is an algorithm used in many NLP and speech recognition models as a final decision making layer to choose the best output given target variables like maximum probability or next output character.
Best Place For was looking for an image recognition based software solution that could be used to detect and identify different food dishes, drinks, and menu items in images sourced from blogs and Instagram. The images would be pulled from restaurant locations on Instagram and different menu items would be identified in the images. This software solution has to be able to handle high and low quality images and still perform at the highest production level, while accounting for runtime as well as accuracy.
Deep learning recommendation system architectures make use of multiple simpler approaches in order to remediate the shortcomings of any single approach to extracting, transforming and vectorizing a large corpus of data into a useful recommendation for an end user.
Let's take a look at the architecture used to build neural collaborative filtering algorithms for recommendation systems
GPT-3 is one of the most versatile and transformative components that you can include in your framework, application or service. However, sensational headlines have obscured its wide range of capabilities since its launch. Let’s take a look at the ways that companies and researchers are achieving real-world results with GPT-3, and examine the untapped potential of this 'celebrity AI'.
How to get started with machine learning based dynamic pricing algorithms for price optimization and revenue management
Let's take a look at how you can use spaCy, a state of the art natural language processing tool, to build custom software tools for your business that increase ROI and give you data insights your competitors wish they had.
The landscape for AI in ecommerce has changed a lot recently. Some of the most popular products and approaches have been compromised or undermined in a very short time by a new global impetus for privacy reform, and by the way that the COVID-19 pandemic has transformed the nature of retail.
Extremely High ROI Computer Vision Applications Examples Across Different Industries
Building Data Capture Services To Collect High ROI Business Data With Machine Learning and AI
Software packages and Inventory Data tools that you definitely need for all automated warehouse solutions
Inventory automation with computer vision - how to use computer vision in online retail to automate backend inventory processes