Ridge Regression Part 2: Deep Dive
Explore Ridge Regression Part 2: Dive into key concepts, Python implementation, and real-world applications for robust linear modeling.
Comment installer la distribution Anaconda pour Python sur Ubuntu 20.04
Anaconda est un gestionnaire de paquets open-source, un gestionnaire d’environnement et une distribution des langages de programmation Python et R. Il est couramment utilisé pour la science des données, l’apprentissage machine, le traitement des données à grande échelle, le…
Few-Shot Prompting: Techniques, Examples, and Best Practices
Learn the fundamentals of few-shot prompting in AI, with key techniques, examples, and best practices to improve model performance and accuracy.
How to run Deepseek R1 LLMs on GPU Droplets
In this article, we will show how to run DeepSeek R1 models on the cloud provider’s GPU Droplets using Ollama.
Training, Validation and Accuracy in PyTorch
In this article, we examine the processes of implementing training, undergoing validation, and obtaining accuracy metrics – theoretically explained at a high level. We then demonstrate them by combining all three processes in a class, and using them to train a convolutional neural network.
Linear Probability Model: Definition, Examples & Limitations
Learn what the Linear Probability Model (LPM) is, with definitions, examples, and key limitations to understand binary outcome predictions.
LoRA: Low-Rank Adaptation of Large Language Models Explained
Learn how LoRA enables efficient fine-tuning of large language models by updating fewer parameters. Explore its benefits, real-world uses, limitations, and future potential.
What’s New with Claude Sonnet 4.6
‘In this tutorial, we examine the powerful, new Claude Sonnet 4.6 model, and show how you can access Sonnet 4.6 today with Gradient!’
Scikit-learn: A Beginner’s Guide to Machine Learning in Python
Learn everything about Scikit-learn, the powerful Python machine-learning library. Explore tutorials and comparisons to master ML with Scikit-learn.
How to Write and Implement Agent Skills
Learn how to create and implement Agent Skills for LLMs using the SKILL.md framework. Build modular, reusable capabilities for AI agents with specialized instructions, Python scripts, and resources. Includes PDF parsing example with PyPDF2 integration.