The Machine Learning Engineer Courses

MLOps MLflow: Deep Learning Frameworks - PyTorch and TensorFlow Integration

Explore integrating deep learning frameworks Pytorch and Tensorflow with MLflow for enhanced model management and tracking.

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

MLOps MLflow: Deep Learning Frameworks PyTorch and TensorFlow in MLflow - Spanish

Aprende a integrar Tensorflow y Pytorch con MLflow para optimizar tus proyectos de Deep Learning y mejorar el seguimiento de experimentos.

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

MLOps MLflow: Time Series Forecasting with SkTime and Prophet

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

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

MLOps MLflow: Time Series Forecasting with SkTime and Prophet in Spanish

Aprende a utilizar SkTime y Prophet para pronósticos de series temporales con MLflow, mejorando tus habilidades en MLOps y análisis predictivo.

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

MLOps MLflow: Installing a MLflow Tracking Server in Docker Containers

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

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

MLOps MLflow: Instalación de Mlflow Tracking Server en Docker Containers con Backend Store MariaDB

Instala y configura un MLflow Tracking Server en contenedores Docker con backend MariaDB para gestionar eficientemente tus proyectos de aprendizaje automático.

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

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.

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

Google App Engine: Deploying ML Applications on Google Cloud

Despliega aplicaciones de Machine Learning en Google Cloud utilizando App Engine. Aprende a configurar, implementar y gestionar soluciones escalables en la nube.

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

Rapids Machine Learning Training and Feature Engineering in GPU with CuML and CuDF

Accelerate ML training and feature engineering using GPU-powered CuML and CuDF libraries for enhanced performance and efficiency.

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

Rapids Machine Learning Training y Feature Engineering en tu GPU con CuML y CuDF

Acelera el entrenamiento de modelos y la ingeniería de características utilizando GPU con CuML y CuDF para optimizar tus flujos de trabajo de aprendizaje automático.

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

Pandas Parallel Transformations with Dask and Pandarallel

Optimize data processing with Dask and Pandarallel for faster Pandas transformations. Learn parallel computing techniques to enhance performance.

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

Pandas Transformaciones en Paralelo con Dask y Pandarallel

Optimiza transformaciones de datos con Dask y Pandarallel para procesamiento paralelo eficiente en Pandas, mejorando el rendimiento en grandes conjuntos de datos.

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

Optimizing Python Code Speed with Numba JIT Compiler

Accelerate Python code execution using Numba's JIT compiler, leveraging jit and njit decorators for enhanced performance.

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

Optimiza la Velocidad de tu Código Python con Numba JIT Compiler

Acelera tu código Python utilizando Numba y los decoradores JIT para optimizar el rendimiento y mejorar la eficiencia computacional.

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

Optimizing Python Code Speed with Functools and NumPy Vectorize

Boost Python code performance using functools and numpy vectorization techniques for faster execution and improved efficiency.

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