MLOps MLFlow: Deployment Server - Managing and Using Multiple LLMs
Install and utilize MLflow Deployment Server to manage multiple LLMs, including OpenAI, Anthropic, and Langchain. Enhance your MLOps skills for efficient model deployment.
MLOps MLFlow: MLflow Projects with PySpark Docker Environments
Explore MLflow Projects with PySpark in Docker, utilizing Databricks for artifact storage and tracking in MLOps workflows.
MLFlow Projects: Dockerized Environments in MLflow
Explore MLflow projects using Docker environments and Databricks for artifact repository and tracking in MLOps workflows.
MLOps: Databricks MLFlow and Optuna Hyper-parameter Tuning
Optimize XGBoost models using Databricks, MLflow, and Optuna for efficient hyperparameter tuning and improved machine learning workflows.
MLOps: Databricks and MLFlow Hyper-parameter Tuning for XGBoost Models
Optimize machine learning models using Databricks and MLflow for hyperparameter tuning with XGBoost and HyperOpt.
MLOps MLFlow: Building Pipelines with MLflow Projects
Build MLflow project pipelines for efficient machine learning workflows. Learn to create and execute data science pipelines using MLflow Projects.
Serving LLMs with MLflow - Phi-3-mini-4k-instruct Model
Aprende a crear, guardar y cargar modelos LLM con MLflow, utilizando Phi-3-mini-4k-instruct para inferencia local en tu computadora.
VertexAI Embeddings with Pinecone and LangChain - Building a Retrieval Component
Aprenda a implementar un componente de recuperación utilizando VertexAI Embeddings, Pinecone y Langchain para aplicaciones de aprendizaje automático y ciencia de datos.
Langchain: Conversational QA Tool with Gemini, Langchain, and Faiss
Crea un chatbot de preguntas y respuestas conversacional utilizando Langchain, Gemini Pro 1.5, Faiss y Vertex AI para consultar una base de conocimientos personalizada.
Langchain: RAG QA Tool with Gemini Pro, Langchain, and Chroma
Develop a RAG-based QA tool using Langchain, Gemini Pro, and Chroma for legal document analysis and retrieval.
LLM Efficient Inference in CPUs and Intel GPUs - Intel Neural Speed
Optimize LLM inference on Intel CPUs and GPUs using Neural Speed. Explore efficient techniques for enhanced performance in machine learning and data science applications.
LLMOps with Langchain, OpenAI, and Faiss on Databricks - Creating a Retrieval QA Tool
Develop a Retrieval QA tool using Langchain, OpenAI, and Faiss. Learn to save components in Databricks' MLFLOW, work with Model Governance, and perform inference after chain retrieval.
ML and MLOps with Databricks: LLMOps, MLFlow, OpenAI, and Databricks
Build a code reviewer using GPT-4, encapsulate it in MLflow, and deploy for inference in Databricks pipelines. Enhance your ML workflow with LLMOps techniques.
LangServe: Creating a RESTful API for Langchain
Create a RESTful API for LangChain runnables and chains, enabling seamless integration of machine learning models into applications.
Langchain: Interacting with APIs Using OpenAI
Explore API interaction using Langchain and OpenAI models for data science and machine learning applications. Learn practical implementation techniques.
Web Scraping with Langchain and OpenAI - Working with HTML Content
Learn web scraping techniques using Langchain and OpenAI, focusing on extracting and processing HTML content for data science and machine learning applications.
Langchain Document Tagging with OpenAI
Create a tool for tagging documents using Langchain and OpenAI, enhancing document organization and retrieval in data science and machine learning projects.
Code Understanding with Langchain, CodeLLama, Llama.cpp and OpenAI
Explore Langchain for Python code understanding, integrating CodeLLama, Llama.cpp, and OpenAI for enhanced machine learning capabilities.
Langchain: Graphs with OpenAI and Neo4J - Data Science and Machine Learning
Explore graph databases using Neo4J, Langchain, and OpenAI for advanced data science and machine learning applications.
Creating and Using Langchain Tools with OpenAI for Data Science and Machine Learning
Create and use Langchain tools with OpenAI for data science and machine learning applications. Learn to integrate powerful AI capabilities into your projects.
Langchain: Working with Structured Data, Databases, and CSV Files
Explore structured data manipulation using Langchain and OpenAI for data science and machine learning applications.