In this tutorial, we explore the TuringEnterprises/Open-MM-RL dataset as a practical foundation for multimodal reasoning and reinforcement learning with verifiable […]
Category: Tutorials
Step by Step Guide to Build and Compare FedAvg and FedProx Federated Learning on Non-IID CIFAR-10 with NVIDIA FLARE
In this tutorial, we build an advanced federated learning experiment with NVIDIA FLARE. We compare FedAvg and FedProx on a […]
Build a Complete Langfuse Observability and Evaluation Pipeline for Tracing, Prompt Management, Scoring, and Experiments
In this tutorial, we implement the Langfuse (an open-source LLM engineering platform) pipeline for tracing, prompt management, scoring, datasets, and […]
Build a SuperClaude Framework Workflow with Commands, Agents, Modes, and Session Memory
In this tutorial, we build an advanced workflow using the SuperClaude Framework as a structured layer on top of the […]
Build Recurrent-Depth Transformers with OpenMythos for MLA, GQA, Sparse MoE, and Loop-Scaled Reasoning
In this tutorial, we explore OpenMythos by building an advanced recurrent-depth transformer workflow that runs end-to-end in Google Colab. We […]
How to Build Knowledge Graph Generation Pipelines From Text With kg-gen, NetworkX Analytics, and Interactive Visualizations
In this tutorial, we will generate knowledge graphs from plain text, conversations, and multiple source documents using kg-gen. We start […]
How to Build an Advanced Agentic AI System with Planning, Tool Calling, Memory, and Self-Critique Using OpenAI API
In this tutorial, we build an advanced agentic AI system using the OpenAI API and a hidden terminal prompt for […]
Stochastic Gradient Descent (SGD’s) Frequency Bias and How Adam Fixes It
Modern language models are trained on data with extremely uneven token distributions. A small number of words appear in almost […]
A Coding Implementation to Compress and Benchmark Instruction-Tuned LLMs with FP8, GPTQ, and SmoothQuant Quantization using llmcompressor
In this tutorial, we explore how to apply post-training quantization to an instruction-tuned language model using llmcompressor. We start with […]
A Coding Guide Implementing SHAP Explainability Workflows with Explainer Comparisons, Maskers, Interactions, Drift, and Black-Box Models
In this tutorial, we implement SHAP workflows as a practical framework for interpreting machine learning models beyond basic feature-importance plots. […]