As you might explain to a friend or adult family member, machine learning is the process of training a computer model using datasets and algorithms. Really, thesealgorithmsthat form the heart of machine learning have been around for decades, but computers have only recently reached the level of ...
In machine learning, we take data (e.g., e-mails), provide information about the desired results (spam and non-spam labels for these e-mails), and feed it to a learning algorithm, which in turn executed by a computer. The computer then learns a set of rules that we can use to aut...
How to Explain AI, Machine Learning and Natural Language Processing Artificial intelligence (AI), machine learning (ML), and natural language processing (NLP) are three of the most powerful technologies that our modern society has access to. Theycan process datain huge quantities in a way that ...
Ridge regression, also known as L2 Regularization, is a regression technique that introduces a small amount of bias to reduce overfitting. It does this by minimizing the sum of squared residualsplusa penalty, where the penalty is equal to lambda times the slope squared. Lambda refers to the se...
This detection uses a machine learning algorithm that reduces B-TP incidents, such as mis-tagged IP addresses that are widely used by users in the organization.TP: If you're able to confirm that the activity was performed from an anonymous or TOR IP address. Recommended action: Suspend the ...
An interview is one of the most versatile methods used in qualitative research. Here’s what you need to know about conducting great qualitative interviews.
All data scientists have a solid foundation in maths and coding, but if you can communicate and articulate clearly, your ideas will have more influence. Being able to explain complex mathematical models like neural networks to non-tech-savvy stakeholders is truly a superpower. You are a ...
” This is extremely important if we are comparing performance metrics on imbalanced datasets, which I will explain in a second (based on the results from Forman & Martin Scholz’ paper).Also, keep in mind that even if our dataset doesn’t seem to be imbalanced at first glance, let’s ...
Step 3 - Monitor and retrain:Explain and observe model behavior and automate the retraining process. The machine learning pipeline orchestrates the process of retraining the model asynchronously. Retraining can be triggered on a schedule or when new data becomes available by calling the published pipel...
▶️ Discover the best strategies for selecting machine learning algorithms tailored to your ML workflows.