Prompt Engineering: OpenAI, GPT-4, and Mistral 7B Basics Introduction
Explore prompt engineering basics with GPT-4, GPT-3.5 Turbo, and Mistral 7B through practical examples and hands-on demonstrations.
Fine-Tuning ViT Classifier with Custom Data and Docker Inference - Part 4
Fine-tune a ViT classifier with custom data and deploy using Docker and FastAPI for efficient image classification in production environments.
Document Summarization: Langchain Summarization Chains, Clustering and LLMs
Explore document summarization using Langchain, Hugging Face Transformers, and clustering techniques for efficient text analysis and insights.
Document Similarity: Langchain Sentence Transformers and Chroma
Explore document similarity using Langchain, HuggingFace Transformers, and Chromadb. Learn to create embeddings and implement vector storage for efficient text analysis and classification.
Installing and Using Ollama Framework for Data Science and Machine Learning
Explore Ollama framework installation, usage, and Python integration for generating, embedding, and chatting with AI models.
DALL-E and Stability.AI: Text-to-Image Models for Data Science and Machine Learning
Explore DALL-E and Stability.AI text-to-image models, learning to generate, edit, and save AI-created images using practical notebooks and hands-on examples.
Computer Vision: OCR Comparison - Tesseract vs PaddleOCR
Explore OCR techniques using Tesseract and alternatives, comparing offline solutions for computer vision and text recognition in data science and machine learning.
Azure AI Computer Vision OCR: Image and Document Intelligence Services
Aprende a utilizar Azure AI Services para OCR de imágenes y documentos con Computer Vision y Document Intelligence.
Google Vertex AI Python SDK and Gemini for Data Science and Machine Learning
Explore Google Vertex AI, SDK, and Gemini through practical demonstrations and hands-on coding examples for machine learning and data science applications.
Langchain Document Summarization Using Fine-Tuned T5 and Clustering
Aprenda a utilizar Langchain para resumir textos usando T5 ajustado e clustering, com demonstração prática e notebooks disponíveis.
Azure ML: Foundation Models Inference Endpoint for Q&A
Explore Azure ML's Model Catalogue and create an Online Inference EndPoint for Foundation QA HuggingFace model predictions. Gain hands-on experience with Azure ML studio and machine learning deployment.
Fine-Tuning Foundation Models with Azure Machine Learning Studio
Fine-tune a BERT foundation model using Azure Machine Learning Studio for enhanced natural language processing capabilities.
Fine-Tuning Foundation Models for Document Classification with Azure ML - LLama2
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.
Deploying a Multimodal Chatbot with Gemini Pro and Streamlit on Google App Engine
Desarrolla un chatbot multimodal con Vertex AI, Gemini Pro y Streamlit, y despliégalo en Google App Engine para aplicaciones de aprendizaje automático.
Neo4J as Vector Store with Langchain, OpenAI, and Wikipedia
Explore Neo4J as a vector store using Langchain, OpenAI embeddings, and Wikipedia data for advanced data science and machine learning applications.
Google App Engine: Deploy Machine Learning Applications in Google Cloud
Deploy machine learning applications on Google Cloud using App Engine. Learn to leverage cloud infrastructure for scalable ML solutions.
ML and MLOps with Databricks: LLMs and HuggingFace Transformers
Explore LLMs using HuggingFace Transformers for summarization, translation, sentiment analysis, and advanced prompting techniques on Databricks.
Neo4J Knowledge Graph: Topic Extraction with Langchain and Phi3 - Part 1
Explore topic extraction for knowledge graphs using Neo4J, Langchain, and Microsoft Phi3. Learn to enrich movie databases with themes from TMDB.org overviews.
CPU Inference with ViT ONNX Model in Azure ML Managed Endpoint - AKS
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.
The Science of LLM Benchmarks: Methods, Metrics, and Meanings
Explore LLM benchmarks, evaluation metrics, and critical assessment techniques to understand model strengths and limitations in this comprehensive talk on AI performance evaluation.
Reliable AI: Successes, Challenges, and Limitations
Explore mathematical approaches to reliable AI, including generalization guarantees, explainability, and applications in imaging and physics, while discussing limitations and connections to novel computing.