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.
MLOps: Crafting Custom Models with Python Model and PyFunc in MLFlow
Craft custom models using MLFlow's PythonModel and pyfunc, enhancing your MLOps workflow with flexible and reusable machine learning components.
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.
Fine-tuning Flan-T5 for Sequence-to-Sequence Classification with MLFlow
Fine-tune Flan-T5 for sequence-to-sequence classification using MLflow. Learn advanced MLOps techniques for optimizing language models in data science projects.
Fine-tuning Flan-T5 for Text Classification with MLFlow
Aprende a personalizar el modelo T5 base para clasificación de secuencias usando tu propio conjunto de datos y MLflow para MLOps.
MLOps with MLflow: Fine-Tuning LLMs - Tracking Experiments and Logging Models
Fine-tune LLMs, track experiments, and log models using MLflow for efficient MLOps practices in data science and machine learning projects.
MLOps: C# Image Recognition with ResNet50v2 Model
Implement image recognition using ResNet50v2 in C# with ONNX and SixLabors.ImageSharp for efficient MLOps workflows.
MLOPS: How to Work with Hugging Face Hub CLI
Aprende a instalar y utilizar la CLI de Hugging Face Hub para gestionar modelos y datasets de aprendizaje automático de manera eficiente.
MLOps: OpenVino Quantized Pipeline for Grammatical Error Correction
Build a grammar error correction model using OpenVino, combining Roberta-based error detection and Flan-T5 correction, with quantization for efficient CPU inference.
Object Detection with Faster R-CNN in C# Using ONNX on CPU
Implement object detection using Faster R-CNN in C# with ONNX format on CPU, leveraging machine learning for efficient image analysis.
How to Get Started with MLOps in Azure Databricks
Explore the machine learning lifecycle and operationalize models using Databricks Machine Learning, focusing on scaling deployments with MLOps for company-wide implementation.
AI-Enabled Chatbot to Production MLOps Application - Red Hat AI Portfolio Demo
Explore Red Hat's AI portfolio: from simple chatbots to full-scale MLOps applications for enterprise. Learn about Podman AI Lab, RHEL AI, and OpenShift AI for building and deploying AI solutions.
The State of Production Machine Learning in 2024
Explore challenges and best practices in production machine learning systems, covering deployment, explanation, security, monitoring, and scaling. Gain insights into the ML tooling ecosystem.
Observability in the MLOps Lifecycle with Prometheus
Explore MLOps monitoring with Prometheus, covering ML deployment challenges, data drift, and model metrics. Learn to enhance existing systems and integrate with tools like Flyte, Seldon Core, and FastAPI.
The Importance of Forgetting for Both Humans and Machines
Explore the crucial role of forgetting in human and machine learning, its impact on adapting to change, and state-of-the-art processes for updating ML models in production environments.
Machine Learning Security Operations at One of the World's Largest Brewing Companies
Explore MLSecOps in brewing industry, focusing on Heineken's approach to automating security in machine learning processes, data democratization, and secure ML workbenches.
How Metaflow Became Netflix's Beloved Data Science Framework
Discover Metaflow, Netflix's ML framework that revolutionized production time. Learn its development, impact, and gain practical insights for your own projects.
Adapting to Change - How Machine Intelligences Adapt to a Changing World
Explore how human and machine intelligences adapt to change, focusing on state-of-the-art techniques in machine learning and MLOps for effective adaptation in AI systems.