How Embedded ML Is Helping To Prevent Wildfires
Devastating wildfires can be prevented with on-device, embedded machine learning.
Localized Environmental Sensing With TinyML
How tinyML provides cost-effective, portable, and localized monitoring of air quality.
Saving The Humble Honey Bee With AI
TinyML is helping to protect honey bees from a vicious, voracious predator.
Roasting Coffee To Perfection Using AI
Perfecting your favorite cup of coffee has gotten easier thanks to AI.
Where Can I Learn Python Online for Free?
Python is one of today’s most sought-after coding skills, and you can learn Python online for free through flexible and self-paced courses taught by leading institutions.
Why the Big Future of Machine Learning Is Tiny
TinyML is an emerging AI technology that promises a big future—its versatility, cost-effectiveness, and tiny form-factor make it a compelling choice for a range of applications.
Real World AI: Checkout-Free Retail (Amazon Go and Zippin)
Checkout-free retail technology is an exciting application of AI that’s changing the way we shop.
Real World AI: Middle Mile Autonomous Delivery (Gatik)
AI is helping to revolutionize the product delivery supply chain through innovative middle mile solutions.
Is Latent Dirichlet Allocation (LDA) A Clustering Algorithm?
How LDA is different—and similar—to clustering algorithms.
What Is Counterfactual Analysis?
Exploring causal relationships by asking ‘what if?’.
What Are Explainable AI Principles?
An introduction to the fundamental principles of explainable AI
What Is LDA Topic Modeling?
A concise, easy-to-follow description of how LDA topic modeling works
Is Topic Modeling Unsupervised?
A clear explanation on whether topic modeling is a form of supervised or unsupervised learning
Explainable AI: What It Is and Why It Matters
An introduction to explainable AI—what it is, why it’s important, and how it works.
Can BERT Understand Fedspeak?
Using NLP and BERT, a state-of-the-art natural language model, to analyze fedspeak, the vauge language used in FOMC meetings.
Topic Model Evaluation
Topic models are widely used for analyzing unstructured text data, but how do you evaluate them? Here’s what you need to know about evaluating topic models.
Topic Modeling with LDA Explained: Applications and How It Works
A step-by-step introduction to topic modeling using a popular approach called Latent Dirichlet Allocation (LDA)
Modeling Topic Trends in FOMC Meetings
Topic modeling can help to analyze trends in FOMC meeting transcripts—this article shows you how.
Topic Modeling of Earnings Calls using Latent Dirichlet Allocation (LDA): Efficient Topic Extraction
Streamline document analysis with this hands-on introduction to topic modeling using LDA
Using Regular Expressions to Search SEC 10K Filings
SEC 10K filings have inconsistencies which make them challenging to search and extract text from, but regular expressions can help