In the rapidly evolving world of web development, certain advancements are reshaping how applications are built and experienced. Among some of the top developments is the integration of machine learning into back-end and UI development. Many factors contribute to this shift, but the most significant lie in the demand for automation, personalization, and interactivity between the platform and users.
These days when someone visits a website they’re looking for quick access to something. When you load up Google or Chat GPT, there’s a search bar waiting for you. It’s no surprise that their infrastructures are powered by machine learning, and it should serve as a benchmark for the transformative impact of machine learning on web development. With that said, let’s look at it in action:
Machine Learning in the Insurance Industry
After looking at a report from McKinsey, it’s clear that the insurance industry will be one of the sectors greatly impacted by machine learning in web development. Instead of the traditional approach of "detect and repair," machine learning enables insurers to shift towards a "predict and prevent" model. This transformation impacts various aspects of the industry, but especially back-end and UI development.
For example, McKinsey outlined that wearable data can be directly integrated with insurance carriers, or connected-home and auto data can be made available through platforms like Amazon, Apple, and Google. What that’s going to do for back-end development is driving the demand for well-rounded data processing and storage systems that are capable of handling real-time data at scale from devices.
On the front of UI development, machine learning is going to need to focus on creating interfaces that are not only visually pleasing but also highly intuitive. For instance, the interface can use interactions from the user to learn and adapt over time which will help with features such as personalizing content recommendations, creating a dynamic user interface, predictive user flow, and that’s just scratching the surface.
“How does this benefit a company's longevity?”
Over the past 3 years, fraud rates have gone up by 70%, risk management is a top priority for companies of all sizes, and website personalization (even for anonymous visitors) is a major draw for consumers.
Machine learning remediates the issues associated with all of this in a few ways. First of all, its ability to analyze data in real-time at scale is something that’s going to detect and prevent fraud like nothing else could. This goes back to the “predict and prevent” model, fraud prevention is all about detecting patterns and anomalies which can save companies from massive attacks.
When it comes to risk management, this is where data-driven machine learning models shine. They take into account multiple data sources and provide risk assessments that are much more efficient than manual analysis and historical data.
Lastly, the personalization aspect comes to life by analyzing user behavior and preferences which the machine learning models can then use to deliver highly tailored content.
When it comes to scalability and adaptability, machine learning is one of those things that truly excels. As data volumes and business complexities grow, the need for systems that can manage and process information at 10x the speed a team of people can becomes critical.
Best Tools Use
What good would this information be without having actionables to implement it effectively? When it comes to leveraging machine learning in web development, having the right tools is crucial. Here are some of the best ones to use:
Gradio
This is a Python library that simplifies building user interfaces for machine learning models. It streamlines UI development and offers an easy-to-use interface for model visualization.
TensorFlow.js
TensorFlow.js is a library best for developing and training ML models in JavaScript. It can be used for both back-end and front-end development and can run in the browser or on Node.js.
TensorFlow
TensorFlow is also very popular for machine learning since it provides a JavaScript library that makes models more efficient. It can help when training and building your models, and you can even run your existing models with the help of the model converter in TensorFlow.js.
Scikit-learn
Scikit-learn is a great machine-learning library that’s used for machine-learning development in Python. Its tools are simple and efficient for data mining and data analysis.
Cortex
Cortex is an open-source platform used for deploying, managing, and scaling machine learning models. It’s going to let you deploy all types of models and is built on top of Kubernetes to support large-scale machine-learning workloads.
MLRun
This is a tool for model development and deployment. It runs in a variety of environments and supports tons of different programming languages such as Python, R, Java, and Go. It can help automate the entire machine learning workflow, with everything from data preparation to model deployment.
Keras
Keras is a high-level neural network API, written in Python and able to run on top of TensorFlow, CNTK, or Theano. It’s meant to enable fast experimentation with deep neural networks and can be used for both research and production.
PyTorch
PyTorch is an open-source machine learning library used for developing and training neural network-based deep learning models. It’s actually primarily been developed by Facebook's AI research group and can be used with Python as well as C++.
Hugging Face
Hugging Face is another open-source library, it provides models for natural language processing (NLP). It can be used for tasks such as text classification, answering questions, and even language translation.
OpenCV
OpenCV is an open-source computer vision library that can be used for image and video processing. It’s got tools for object detection, face recognition, and various other computer vision tasks.
The Takeaway
Machine learning is going to be the greatest driving force behind the future of technology and innovation. We can give you the tools, but without a proper strategy, you’re a gardener in a war. We want you to be the warriors in a garden of possibilities which is why ISU Corp is offering AI consulting services. With our expertise and experience in the realm of AI and machine learning, we can work closely with your organization to craft a tailored AI strategy that aligns with your objectives and needs to excel in your industry.
Written By Ben Brown
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ISU Corp is an award-winning software development company, with over 17 years of experience in multiple industries, providing cost-effective custom software development, technology management, and IT outsourcing.
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