The Machine Learning Engineer Courses

Google ML and AI - How to Use OpenAPI Tools with Google ADK Agents

2 ratings

Discover how to build conversational assistants using Google Agent Development Kit with OpenAPI tools to query SQL databases through natural language interactions.

• YouTube
• 40 minutes
• Self-Paced
• Free Video

Azure ML: Python SDK v2 - Creating Machine Learning Applications

1 rating

Develop ML applications using Azure Machine Learning Studio Python SDK v2. Train models and publish to Azure ML model repository.

• YouTube
• 1 hour 4 minutes
• Self-Paced
• Free Video

LLMOps: Comparación de Openvino, ONNX, TensorRT y Pytorch para Inferencia

Compara el rendimiento de inferencia de modelos convertidos a ONNX, OpenVino y TensorRT frente a PyTorch nativo en GPU y CPU.

• YouTube
• 39 minutes
• Self-Paced
• Free Video

LLMOps: OpenVino Toolkit Quantize to 4int LLama 3.1 8B Inference on CPU

Convert and quantize LLAMA3.1 8B model to OpenVINO format for efficient CPU inference. Learn model optimization techniques for improved performance.

• YouTube
• 24 minutes
• Self-Paced
• Free Video

MLOps: OpenVino Quantized Model for Grammar Typo Detection

Develop a grammar typo detection model using DistilBERT, fine-tune with Neuspell, and optimize for CPU inference with OpenVINO.

• YouTube
• 21 minutes
• Self-Paced
• Free Video

MLOps: OpenVino Quantized Model para Detección de Errores Tipográficos

Construye un modelo de detección de errores tipográficos utilizando DistilBERT, personalízalo con neuspell y optimízalo con OpenVINO para inferencia eficiente en CPU.

• YouTube
• 21 minutes
• Self-Paced
• Free Video

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.

• YouTube
• 55 minutes
• Self-Paced
• Free Video

MLOps: OpenVino Quantized Pipeline for Grammatical Error Correction

Construye un modelo de corrección gramatical con detector Roberta y corrector Flan-T5, optimizando con OpenVINO y cuantización para mayor eficiencia.

• YouTube
• 50 minutes
• Self-Paced
• Free Video

LLMOps: Converting Microsoft Florence2 Models to OpenVINO IR Format

Convert Microsoft Florence2 to OpenVino IR format and explore its multitask multi-prompt vision capabilities for enhanced machine learning applications.

• YouTube
• 51 minutes
• Self-Paced
• Free Video

LLMOps: Convertir Modelos Microsoft Florence2 a Formato OpenVino IR

Convierte modelos Microsoft Florence2 a formato OpenVino IR y explora sus opciones en una demostración práctica.

• YouTube
• 46 minutes
• Self-Paced
• Free Video

MLOps: OpenVino Toolkit - Compress and Quantize YOLO Model

Convert and quantize YOLOv10 to OpenVINO IR format, then perform inference on CPU with YOLOv10 and YOLOv8 for optimized machine learning deployment.

• YouTube
• 58 minutes
• Self-Paced
• Free Video

MLOps: Compresión y Cuantización de Modelos YOLO con OpenVino Toolkit

Convierte y optimiza modelos YOLO con OpenVINO: comprime, cuantiza y realiza inferencias eficientes en CPU para mejorar el rendimiento de detección de objetos.

• YouTube
• 49 minutes
• Self-Paced
• Free Video

Language Detection in Python and C# for MLOps and NLP

Implement language detection in Python and C# using CLD3, LangDetect, and FastText libraries for NLP and machine learning applications.

• YouTube
• 33 minutes
• Self-Paced
• Free Video

MLOps NLP: Language Detection in Python and C#

Aprende a detectar idiomas en texto usando librerías como CLD3, LangDetect y FastText en Python y C#. Explora técnicas de NLP para ciencia de datos y aprendizaje automático.

• YouTube
• 44 minutes
• Self-Paced
• Free Video

LLMOPs: Inference in CPU with Microsoft Florence 2 ONNX Model Using C#

Explore CPU inference using Microsoft Florence 2 Large ONNX model in C#. Learn practical implementation for data science and machine learning projects.

• YouTube
• 29 minutes
• Self-Paced
• Free Video