Browsing: Learning

Job descriptions of Data Engineering roles have changed drastically over the years. In 2026, these read less like data plumbing and more like production engineering. You…

Are you following the trend or genuinely interested in Machine Learning? Either way, you will need the right resources to TRUST, LEARN and SUCCEED. If you…

Nous Research has introduced NousCoder-14B, a competitive olympiad programming model that is post trained on Qwen3-14B using reinforcement learning (RL) with verifiable rewards. On the LiveCodeBench…

Image by Editor   # Introduction  Machine learning practitioners encounter three persistent challenges that can undermine model performance: overfitting, class imbalance, and feature scaling issues. These problems…

In this tutorial, we demonstrate a realistic data poisoning attack by manipulating labels in the CIFAR-10 dataset and observing its impact on model behavior. We construct…

What does an end to end stack for terminal agents look like when you combine structured toolkits, synthetic RL environments, and benchmark aligned evaluation? A team…

Image by Author   # Introduction  Learning AI today is not just about understanding machine learning models. It is about knowing how things fit together in practice,…

In machine learning with categorical data, it is common to encode the categories as dummy variables (sometimes called one hot encoding) to encode categories as numerical…

In machine learning and data science, evaluating a model is as important as building it. Accuracy is often the first metric people use, but it can…

Liquid AI has introduced LFM2-2.6B-Exp, an experimental checkpoint of its LFM2-2.6B language model that is trained with pure reinforcement learning on top of the existing LFM2…