Building Production-Grade spaCy Text Classification Pipelines for Business Data
Unlock the full potential of spaCy with this guide to building production-grade text classification pipelines for business data.
Width.ai helps warehouses and other inventory storing businesses automate out and optimize huge chunks of their entire business process (yes entire, seriously, we’ve seen 22%+ easy) by building custom software solutions for warehouse automation that use machine learning and computer vision. One of the most important parts of growing your inventory business is being able to scale efficiently and optimize your warehouse space to store your cash-growing asset (inventory). These automations allow you to completely remove these hours from your inventory cycle, making you insanely profitable. There are several tools we use that help companies build these automation systems that you must have in 2020 if you are serious about scaling your warehouse or inventory and automating your business.
In terms of automation, this python library is going to be one that you turn to quite a bit. With the large increase in robotics in warehousing, computer vision is becoming one of the most important tools needed. No matter who is on the floor managing inventory, man or robot, you need a way to quickly read labels and barcodes to pass data and information to backend systems, or to alert suppliers of what product you’ve received and which orders are finished. The robust nature of OpenCV allows you to solve much trickier computer vision problems in the warehouse, like custom labels and lots of SKUs, and gives you pretty in-depth functions that really allow you to customize your computer vision based reader. Personally we’ve seen this work really well with noisy labels that are hard for other libraries and tools to extract the information needed. As upstream product manufacturers change the label format, move barcodes and remove fields, your label reading system adjusts and learns the new formats. If you’re a company that has large inventory or a warehouse looking to add computer vision to your arsenal, OpenCV is a great place to start.
Most custom automation solutions built for warehousing, especially machine learning and computer vision based ones, can become quite large and difficult to run as they scale in size (both the warehouse and the system). What you’ll find is that the normal office computer running your backend system will start to struggle and slow down your now newly built warehouse automation systems. Most of the time, moving to amazon web services to manage your software becomes the best route to take, given how inexpensive it is to run incredibly robust warehouse automation software solutions. You never want to take the chance you can’t complete an order on time or can’t instruct a robot what to do because your system can’t finish its run for you. Most of these tools being used in your automation are too powerful for a normal computer to run in a quick manner, and having dedicated servers in AWS is a great way to outsource these tools so you can continue on without seeing the effects. Most of the time you can set up your AWS configuration to only spend when it needs to, and keep a super cheap baseline the rest of the time. The custom nature of what a development company or firm will build means they will be more inclined to set up AWS to run your system, over a company that sells software as a bundled product.
For creating almost any long term automated warehouse solutions, being able to predict and forecast your current and future inventory levels is as important as it sounds. Eliminating inventory shortages and understanding what causes surplus is a vital part of any automation or warehouse optimization solution and can give you seriously profitable results within the first hour it’s built. Facebook Prophet is a time-series forecasting model that lets you do exactly what’s described above, gives you forecasting on where your inventory levels will be, and always adjusts to new data to allow you to be super precise with when you need to restock. We’ve taken this tool in the past and used it to give even deeper insights into inventory, allowing you to predict holiday season sales, least profitable products over an upcoming year, profitability of each square inch of inventory and so many more. The reason I put this after AWS is for a very specific reason. AWS will allow you to collect lots of data and give you a place to store it, which is needed for to give these predictions in the forecasting model.
One of the most important parts of most warehouse automation solutions is having the ability to automate decision making. Once you’ve got your warehouse data analytics and inventory information on the current status of everything related to your business, it's time to see the effects of true deep analytics kick in. Decision trees allow you to make calculated, smart decisions based on the information you’ve already collected, like a last step in a fully automated warehouse system. There are plenty of libraries that offer decision trees, my favorite being scikit learn, and lots of different versions of them for you to test out and find the best solution for your business. If you plan on using multiple ai models and tools to do a bunch of tasks in your warehouse, using some form of decision trees is a great way to help make your final decisions with the new ai analysis.
Note: Partially automated warehouse systems might not always need decision trees as being part of a final step, mostly when a user still has to input.
While your automation journey might not need these specific tools, and will probably require way more than just these libraries. It’s good to understand the most common things that are being used in your custom ai system and why they are there. And while there's many more things you will need, and we didn’t even discuss floor spacing optimization or much around that. These are the beginner tools needed to start moving to a fully automated warehouse system. I definitely suggest taking a look at this inventory management case study to understand how flexible these libraries are for anything related to building warehouse automation solutions
Are you a business that has a few warehouses or complex inventory that's hard to keep track of? Want a solution that’s completely customized for you, not some giant corporate solution that costs a fortune?
Do what other businesses do: https://www.width.ai/#contact
Let’s talk about showing you our custom warehouse automation systems!
A little bit about Width.ai:
We are a machine learning and data science consulting firm focused completely on building business tools to increase profitability for clients. We specialize in natural language and computer vision systems that allow us to build software solutions for warehouse automation and other sectors of business.
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.
Automatically categorize your Shopify store products to the Shopify Product Taxonomy instantly with ai based PIM software
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 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
Inventory automation with computer vision - how to use computer vision in online retail to automate backend inventory processes