Tutorials

Auto Added by WPeMatico

IMDb Sentiment Analysis with DistilBERT LoRA, TF-IDF Baselines, Calibration, Interpretability, Robustness Testing, and Semi-Supervised Learning

ai, AI (Artificial Intelligence), Applications, Artificial Intelligence, deep learning, Editors Pick, Machine Learning, Staff, Technology, Tutorials

In this tutorial, we develop an end-to-end sentiment analysis workflow using the Stanford NLP IMDb Large Movie Review Dataset and compare classical machine learning with parameter-efficient transformer fine-tuning. We begin by establishing a reproducible environment and auditing the dataset for class ordering, review-length skew, duplicate leakage, and preprocessing artifacts before training a strong TF-IDF and

IMDb Sentiment Analysis with DistilBERT LoRA, TF-IDF Baselines, Calibration, Interpretability, Robustness Testing, and Semi-Supervised Learning Read More »

Designing Scalable Interactive Visualizations with Reflex XY: Composition, Million-Point Rendering, Streaming, Custom Marks, and Export

ai, AI (Artificial Intelligence), Artificial Intelligence, Data Visualization, Databases, Editors Pick, Staff, Technology, Tutorials

In this tutorial, we explore the advanced visualization capabilities of the XY Python library by building interactive, scalable, and extensible charts. We begin with XY’s composition model, where we combine multiple marks, dual axes, annotations, tooltips, legends, themes, and interactive controls within a single chart declaration. We then work with Pandas DataFrames, faceted layouts, linked

Designing Scalable Interactive Visualizations with Reflex XY: Composition, Million-Point Rendering, Streaming, Custom Marks, and Export Read More »

Building a Multimodal RAG Pipeline with NVIDIA NeMo Retriever, Hosted NIMs, LanceDB, Reranking, and Grounded Generation

ai, AI (Artificial Intelligence), AI Infrastructure, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Staff, Technology, Tutorials

In this tutorial, we build an advanced multimodal retrieval-augmented generation pipeline with NVIDIA NeMo Retriever. We begin by configuring a Python 3.12 environment, installing the required packages, and performing offline PDF text extraction without relying on a GPU or external API key. We then extend the workflow with hosted NVIDIA NIM endpoints to detect page

Building a Multimodal RAG Pipeline with NVIDIA NeMo Retriever, Hosted NIMs, LanceDB, Reranking, and Grounded Generation Read More »

Adaptive Experimentation with Meta’s Ax: A Practical Coding Guide

ai, AI (Artificial Intelligence), Applications, Artificial Intelligence, Computer vision, Editors Pick, Technology, Tutorials

In this tutorial, we explore adaptive experimentation using Meta’s Ax with the modern Client API. We work through a complete workflow where we tune a RandomForest model on a synthetic classification dataset while balancing predictive accuracy against model footprint. We begin by defining a mixed search space with integer, float, log-scaled, and categorical parameters, then

Adaptive Experimentation with Meta’s Ax: A Practical Coding Guide Read More »

End-to-End Bayesian Marketing Mix Modeling with Google Meridian: Media Measurement, ROI Analysis, and Budget Optimization

ai, AI (Artificial Intelligence), AI Infrastructure, Applications, Artificial Intelligence, Editors Pick, Staff, Technology, Tutorials

In this tutorial, we build a complete Bayesian marketing mix modeling workflow using Google Meridian. We begin by installing the required libraries, verifying GPU availability, and exploring a geo-level marketing dataset that includes media impressions, spend, controls, promotions, conversions, population, and revenue. We then map the raw columns to Meridian’s data schema, define interpretable ROI-based

End-to-End Bayesian Marketing Mix Modeling with Google Meridian: Media Measurement, ROI Analysis, and Budget Optimization Read More »

Pixel-Native RAG: A Practical Guide to Visual Document Indexing

ai, AI (Artificial Intelligence), Artificial Intelligence, Editors Pick, Language Model, Large Language Model, model context protocol, Staff, Technology, Tutorials

In this tutorial, we build a complete pixel-native retrieval-augmented generation pipeline from scratch and examine how document retrieval works without relying on conventional HTML parsing, text extraction, or fixed chunking strategies. We render web pages and PDF documents as images, divide them into overlapping tiles, generate multimodal embeddings with SigLIP, CLIP, or an optional Qwen3-VL

Pixel-Native RAG: A Practical Guide to Visual Document Indexing Read More »

Building an Advanced AI Skill Security Auditing Pipeline with NVIDIA SkillSpector, LangGraph, YARA Rules, SARIF, and CI Policy Gates

agentic ai, ai, AI (Artificial Intelligence), AI Agents, Applications, Artificial Intelligence, Editors Pick, Language Model, New Releases, Software engineering, Staff, Technology, Tutorials

In this tutorial, we build a workflow for evaluating the security posture of AI skills with NVIDIA SkillSpector. We create a synthetic skill marketplace containing clean, risky, malicious, and MCP-based examples, then scan each skill through SkillSpector’s LangGraph inspection pipeline. We examine risk scores, categorized findings, confidence levels, analyzer completeness, and executable-script indicators before organizing

Building an Advanced AI Skill Security Auditing Pipeline with NVIDIA SkillSpector, LangGraph, YARA Rules, SARIF, and CI Policy Gates Read More »

Evaluating Multimodal Vision Models with Moonshot PerceptionBench Using Robust Data Loading and Automated Judging

agentic ai, ai, AI (Artificial Intelligence), AI Infrastructure, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Staff, Technology, Tutorials

In this tutorial, we design an end-to-end evaluation workflow for PerceptionBench. This multimodal benchmark measures fine-grained visual perception capabilities across tasks such as OCR, counting, localization, contextual reasoning, comparison, depth understanding, and hallucination detection. We begin by configuring a Colab-compatible environment, installing the required libraries, and loading a balanced subset of the dataset through a

Evaluating Multimodal Vision Models with Moonshot PerceptionBench Using Robust Data Loading and Automated Judging Read More »

A Tutorial on GeoAI: Designing Footprint Extraction from NAIP Imagery Using U-Net, Grounding DINO, SAM, and Mask R-CNN

ai, AI (Artificial Intelligence), Artificial Intelligence, Computer vision, Editors Pick, Staff, Technology, Tutorials

In this tutorial, we design a complete GeoAI workflow for extracting building footprints from high-resolution NAIP aerial imagery. We begin by configuring the geospatial deep learning environment, downloading raster imagery and vector labels, and inspecting their spatial properties before generating georeferenced image chips and segmentation masks. We then train a U-Net model with a ResNet-34

A Tutorial on GeoAI: Designing Footprint Extraction from NAIP Imagery Using U-Net, Grounding DINO, SAM, and Mask R-CNN Read More »

End-to-End Forecasting with TimesFM 2.5: Backtesting, Covariates, Anomaly Detection, and Scalable Colab Deployment

ai, AI (Artificial Intelligence), Artificial Intelligence, Editors Pick, Machine Learning, Staff, Technology, Tutorials

In this tutorial, we build an advanced end-to-end time-series forecasting workflow with TimesFM 2.5. We begin by configuring the runtime, installing the required dependencies, detecting available hardware, and generating a realistic multi-store retail dataset with trend, seasonality, pricing, promotions, holidays, temperature effects, and random variation. We then load and compile the TimesFM 2.5 model, examine

End-to-End Forecasting with TimesFM 2.5: Backtesting, Covariates, Anomaly Detection, and Scalable Colab Deployment Read More »