H100 vs. Other GPUs: A comprehensive guide to selecting the ideal GPU for your machine learning workloads, exploring the unique advantages of NVIDIA’s H100 over competing options.
Learn how to build AI-powered applictions, as I show you in this tutorial, how I built a full-stack travel app using the Gradient platform
TensorFlow is an open-source machine learning software built by Google to train neural networks. In this tutorial, you’ll install TensorFlow in a Python virtual environment. You’ll then validate your installation by running a short TensorFlow program and then use TensorFlow to perform image recognition.
In this article, we will understand what is batch inferencing and demonstrate on how to do that using DigitalOcea’s 1-Click Model
Neural networks achieve state-of-the-art accuracy in many fields such as computer vision, natural-language processing, and reinforcement learning. In this tutorial, you’ll specifically explore two types of explanations: 1. Saliency maps, which highlight the most important parts of the input image; and 2. decision trees, which break down each prediction into a sequence of intermediate decisions.
This tutorial works through a step-by-step example of how to implement the Levenshtein distance in Python for word autocorrection and autocompletion.
An introduction to Triton Programming. In this article, we discuss Triton, a python DSL and compiler for accelerating AI workloads.
Explore the LangMem SDK for agent long-term memory features, architecture, and how it enables persistent, context-aware AI agents.
Understand logistic regression with Scikit-Learn. Learn key concepts, implementation steps, and best practices for predictive modeling.
Explore MobiLlama, SLM essentially a scaled-down versions of Llama, featuring 0.5 billion parameters, in contrast to LLMs that boast hundreds of billions or even trillions of parameters.
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