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Learn how to build generative AI applications and solutions using watsonx, with the guides published by AI experts on IBM Developer.

Building data pipelines using natural language with Data Prep Kit (DPK)

Mohammad Nasser, Revital Sur, Alexey Roytman, Aanchal Goyal

Preparing data for an agentic workflow

Mohammad Nasser, Revital Sur, Alexey Roytman, Aanchal Goyal

Extract text from documents using watsonx.ai TextExtraction API

Nidhi Jain

Boosting Document Intelligence

Ela Dixit, Deepa Amasar

Extracting, classifying, and summarizing documents using LLMs

Salvatore DeDona, Luke Harrison

Contributing knowledge to open-source LLMs like the Granite models using the InstructLab UI

Ahmed Azraq

Improve your RAG solution by converting natural language queries to Elasticsearch SQL by using watsonx.ai

Aditya Mahakali, Mohith Charan

Contributing knowledge to the open source Granite model using InstructLab

Ahmed Azraq

Deploying LLMs tuned with Parameter-Efficient Fine-Tuning (PEFT) techniques in watsonx.ai

Saloni Saluja

Top 3 reasons to register for Open Source LLMs Dev Day

Michelle Kovac, Neil MacKinnon

Build an agentic framework with CrewAI memory, i18n, and IBM watsonx.ai

Paarttipaabhalaji Manohar

Five ways to use the new Granite 3.2 models

Bill Higgins, Anthony Colucci

Last chance for early-bird pricing for IBM TechXchange 2025!

Neil MacKinnon

AI model training with PyTorch

Kiersten Stokes, Mike Brown, Sahdev Zala, BJ Hargrave

Enhancing AI retrieval with HNSW in RAG applications

Niranjan Khedkar

The open source ecosystem of watsonx

Maureen McElaney

Highlights from IBM TechXchange Dev Day: Virtual Agents!

Neil MacKinnon

Build a multilingual language detection and translation system using IBM watsonx.ai

Bhavishya Pandit

Optimizing LLMs with cache augmented generation

Gautam Chutani, Anupam Chakraborty

Build OpenAI-like web agents using IBM watsonx.ai