Analysts like IDC and Deloitte estimate that up to 80% of the world’s data is unstructured text data, which makes getting valuable insights out of this type of data a huge challenge. Worse, customers can’t easily find the right answers to address their product and service-related questions that are hidden in large amounts of support documents. As a result, employees […]
Create a Thorough Plan and Training Strategy for Citizen Data Scientists
As a business owner, executive, or manager, you are likely aware of the term “citizen data scientists.” Perhaps you have even implemented this type of initiative in your organization. While business journals and industry and technology publications discuss the advantages of the citizen data scientist approach, many businesses fail to get the most out of […]
Data Science and Privacy: Defending Sensitive Data in the Age of Analytics
When big data began getting corporate attention in the late 2000s, the idea of data privacy was considered lavish and exotic. The public was less concerned about securing their data assets and was only fascinated by the fact that the interconnected digital world would change their lives forever. As we soon step into 2023, the […]
Interactive Bioactivity Prediction with Multitask Neural Networks
A CHEMBL-OG post, Multi-task neural network on ChEMBL with PyTorch 1.0 and RDKit, by Eloy, from way back in 2019 showed how to use data from ChEMBL to train a multitask neural network for bioactivity prediction – specifically to predict targets where a given molecule might be bioactive. Eloy has links to more info in his […]
An Introduction to Reinforcement Learning
In this blog post, I’d like to introduce some basic concepts of reinforcement learning, some important terminology, and a simple use case where I create a game playing AI in my company’s analytics platform. After reading this, I hope you’ll have a better understanding of the usefulness of reinforcement learning, as well as some key […]
How to Make the Jump to AI
AI and machine learning models are being used to help companies stay competitive by discovering new revenue opportunities, improving risk management, detecting fraud, and streamlining business processes. But years ago, data science wasn’t even on the curriculum at universities, so many software engineers are acquiring the necessary skills on their own. From my experience, anyone who […]
3 Common Business Intelligence Challenges
Typical business intelligence implementations allow business users to easily consume data specific to their goals and daily tasks. The ability to analyze both past and present events unlocks information about the current state and is essential for remaining competitive in today’s data-forward market. With that in mind, there are some common business intelligence challenges that […]
OSINT Basics for Safety and Profit
The internet is the world’s largest information database. Inside the giant mountain of data it contains, there are insights and tools to inform just about any issue your organization might be having. The problem is, when confronted with the issues, you can’t simply brandish the whole mountain in defense. To carve out the correct tools, […]
Is Your Business Ready for Data Science?
As data science and AI technologies become more integrated into everyday business processes, more and more companies are seeing their tremendous benefits. But there are challenges with successfully deploying AI in a manner that drives measurable business outcomes. I wanted to share with you some of the best ways to address those challenges and help […]
Training a Machine Learning Model to Building a Predictive Web Application in Three Easy Steps
Do you remember when we took you through the nine circles of hell with parameter optimization and a cup of tea? We introduced a parameter optimization workflow that uses four different machine learning models, individually optimizes the hyperparameters, and picks the best combination of machine learning method and hyperparameters for the user. However, the usual data scientist journey […]