Deep Learning is a category of machine learning with special advantages for some tasks and disadvantages for others. Machine learning workflows begin by identifying features within data sets. For structured information with relatively few columns and rows, this is straightforward.
Classifications are the most frequently used—and most useful—prediction types. Classifications are predictions that separate data into groups. Binary Classification produces “yes-no” or “in-out” answers when there are only two choices. Multi-Class Classification applies when there are three or more possibilities and shows probabilities
Predictions are interesting on their own. They are valuable when put into production. Operationalizing AutoML – often called “ML Ops” – means putting AutoML predictions into regular workflows to change business outcomes. Here are a few ways do it. Graphical
Productive uses for AI are closer at hand than ever due to the rise of AutoML. Beginning in 2019, advancements in AI have replaced obstacles with tools to benefit from its power. Foremost among them is Automated Machine Learning (AutoML), which does
Follow the money to see why marketing and sales are the most common applications for AI. Instant PaybackSmall improvements in marketing and sales can produce large returns quickly. Think of the impact of gaining a few percentage points on lead conversions,
Statistics and machine learning differ in method and purpose. Which is superior depends upon your goals. Statistics is a subset of mathematics that interprets relationships among variables in data sets. Statisticians make inferences and estimate values based solely on data collected
How Important Is Explainability? Understanding the inner workings of ML algorithms may distract from realizing benefits from good predictions. Explainability Explained With the rise of artificial intelligence has come skepticism. Mysteries of how AI works make questioning the “black box”
Showing the way vs. stumbling in the dark – there are applications for both. Supervised Supervised Learning shows AutoML algorithms sets of known outcomes from which to learn. Think of classroom drills, or giving a bloodhound the scent. Supervised learning
What Is A Confusion Matrix? The most aptly named AI term is actually simple. A Confusion Matrix is a table that shows how often an AI classifier gets confused predicting true and false conditions. Here is a simple example of
Earlier this year, Brett House of Nielsen and Judah Phillips from Squark presented at Analytics Nexus 2019. Here is a transcript of Brett’s remarks. Watch the video “Thank you, Judah. To quickly introduce myself, as Judah had mentioned, I run
Squark is a no-code predictive analytics SaaS that automatically analyzes business data you work with every day to predict customer outcomes, uncover new and unforeseen business opportunities, and mitigate risk. It is a simple and easy-to-use AI software that doesn’t require data science nor technical expertise. In a matter of clicks, make confident, data-backed decisions about what your customers will do next and understand why to increase your business impact.