A loss function is a key concept in machine learning. It measures how well a model’s predictions match the actual outcomes. The loss function calculates the difference between predicted values and true values, which is called “ground truth.” A smaller…
In this article, we’ll look at ways to determine how much data you need to train an AI model with satisfactory results. Defining the right amount of data to train an Artificial Intelligence is a tricky venture. Indeed, it’s complex…
Here, I’ll show you how to install and use cuML on Google Colab to boost the training speed of your Machine Learning models. Google Colab offers cloud-based notebooks for running Python code. Mostly used by Data Scientists and ML Engineers,…
In this article, I present you the options, their benefits and drawbacks, for integrating AI into your business. Using Artificial Intelligence in 2024 has become a major issue for companies aiming to remain competitive. Today, there are 3 main options…
In this article, I unveil the secrets of Bayesian Optimization, a revolutionary technique for optimizing hyperparameters. Hyperparameters play an essential role in the performance of Machine Learning models. However, finding the optimal combination of hyperparameters can be a daunting task.…
On April 04, 2023, I reached TOP 1 in a Kaggle competition ranking. I share everything with you in this article! Kaggle is a website that allows anyone to participate in Machine Learning competitions. The goal is simple: build the…