
Create and deploy a multi-component pipeline with Azure ML, including component registration, data management, and Batch Endpoint setup for efficient machine learning workflows.

Fine-tune a BERT foundation model using Azure Machine Learning Studio for enhanced natural language processing capabilities.

Fine-tune LLM for document classification using Azure ML Studio's Python SDK. Learn to adapt Llama2, Mistral, or other models for text classification tasks.

Explore centrality algorithms in Neo4J Graph Data Science Library for advanced network analysis and machine learning applications.

Explore Neo4J GDS library's similarity algorithms for data science and machine learning, with practical demonstrations and code examples.

Explore data pre-processing and feature engineering using Neo4J's Graph Data Science Library for enhanced machine learning workflows.

Crea pipelines de clasificación de nodos con Neo4J y Graph Data Science Library para aprender técnicas avanzadas de machine learning en grafos.

Desarrolla un chatbot multimodal con Vertex AI, Gemini Pro y Streamlit, y despliégalo en Google App Engine para aplicaciones de aprendizaje automático.

Explore Neo4J as a vector store using Langchain, OpenAI embeddings, and Wikipedia data for advanced data science and machine learning applications.

Explore Vertex AI's Model Garden, deploy LLama3 8B to an Inference Endpoint, and consume it using Python SDK. Gain hands-on experience with advanced machine learning tools.

Deploy machine learning applications on Google Cloud using App Engine. Learn to leverage cloud infrastructure for scalable ML solutions.

Install and configure MLflow Tracking Server with MariaDB backend using Docker containers for efficient MLOps workflows.

Explore time series forecasting using SkTime and Prophet libraries in MLflow, enhancing your MLOps skills with practical implementation.

Explore topic extraction for knowledge graphs using Neo4J, Langchain, and Microsoft Phi3. Learn to enrich movie databases with themes from TMDB.org overviews.

Explore Azure AI and OpenAI Studio, learn Python SDK usage, and discover practical examples for machine learning and data science applications.

Deploy ONNX models to Azure ML Managed Endpoints (AKS) for efficient inference. Learn step-by-step process using Python SDK v2 to optimize machine learning operations.

Deploy a Vision Transformer model for CPU inference on Azure Kubernetes Service using ONNX format and Azure ML SDK v2. Learn to create managed endpoints in Azure ML Studio.

Aprenda a implementar un modelo ViViT en ONNX para inferencia en CPU utilizando Azure Kubernetes Services y onnxruntime con Python SDK v2.

Explore open-source multimodal embeddings for cross-modal search and MM-RAG. Learn techniques for integrating diverse data types, enhancing decision-making with real-time processing and LLMs.

Explore comparative analysis of amyloid fibril fragmentation stabilities, crucial for understanding neurodegenerative diseases. Learn analytical approaches to assess polymorphic structures under mechanical perturbation.

Discover how open-source projects like FreeBSD can boost your development career. Learn about community-driven development, essential skills, and ways to contribute effectively to open-source initiatives.