Distributed Training Courses and Certifications

Building End-to-end Machine Learning Workflows with Kubeflow

27 ratings at Pluralsight

In this course, you will learn how to effectively build end-to-end scalable, production grade machine learning workflows using Kubeflow.

• Pluralsight
• 3 hours 31 minutes
• On-Demand
• Free Trial Available

Deep Learning Using TensorFlow and Apache MXNet on Amazon Sagemaker

14 ratings at Pluralsight

This course is an in-depth introduction to SageMaker and the support it offers to train and deploy machine learning models in a distributed environment.

• Pluralsight
• 2 hours 22 minutes
• On-Demand
• Free Trial Available

TensorFlow

Inside TensorFlow

Deep dive into TensorFlow's internal workings, covering advanced topics like parameter servers, quantization, debugging, and optimization, presented by the framework's developers.

• YouTube
• 17 hours
• On-Demand
• Free Video

Deploying PyTorch Models in Production: PyTorch Playbook

This course covers the important aspects of performing distributed training of PyTorch models, using the multiprocessing, data-parallel, and distributed data-parallel approaches. It also discusses which you can host PyTorch models for prediction.

• Pluralsight
• 2-3 hours
• On-Demand
• Free Trial Available

Architecting Production-ready ML Models Using Google Cloud ML Engine

This course covers Cloud ML Engine, a powerful service that supports distributed training and evaluation for models built in TensorFlow, Scikit-learn and XGBoost.

• Pluralsight
• 2 hours 12 minutes
• On-Demand
• Free Trial Available

Amazon SageMaker Technical Deep Dive Series

Comprehensive deep dive into Amazon SageMaker, covering notebook instances, algorithms, custom models, training, deployment, tuning, and advanced features for efficient machine learning workflows.

• YouTube
• 4 hours 30 minutes
• On-Demand
• Free Video

TensorFlow

Inside TensorFlow - tf.data + tf.distribute

Explore best practices for tf.data and tf.distribute in TensorFlow, covering input pipelines, performance optimization, and distributed training strategies for multi-GPU and TPU setups.

• YouTube
• 46 minutes
• On-Demand
• Free Video

TensorFlow

Deep Learning for Fundamental Sciences Using High-Performance Computing

Exploring deep learning applications in fundamental sciences using high-performance computing to uncover universe secrets and improve discovery sensitivity.

• YouTube
• 27 minutes
• On-Demand
• Free Video

TensorFlow

Distributed TensorFlow Training - Google I/O 2018

Learn to scale TensorFlow training across multiple GPUs and machines efficiently. Explore distribution strategies, performance optimization techniques, and practical implementation using Google Cloud.

• YouTube
• 35 minutes
• On-Demand
• Free Video

Meta

Introducing PyTorch 1.0 - A Research-Focused, Production-Ready Deep Learning Framework

Explore PyTorch 1.0, a powerful deep learning framework that bridges research and production, accelerating AI development with innovative features and tools.

• YouTube
• 40 minutes
• On-Demand
• Free Video

Open Data Science

Build NLP Model with Azure ML AutoML NLP Capability

Learn to build NLP models using Azure ML AutoML for tasks like classification and named entity recognition. Explore multilingual support, data labeling, and distributed training for efficient model development.

• YouTube
• 33 minutes
• On-Demand
• Free Video

Databricks

Generalized Pipeline Parallelism for DNN Training - PipeDream System Overview

Efficient multi-accelerator parallelization for DNN training using PipeDream, combining intra-batch parallelism with inter-batch pipelining to improve throughput and overcome challenges in bi-directional training.

• YouTube
• 21 minutes
• On-Demand
• Free Video

Databricks

Scaling Up AI Research to Production with PyTorch and MLFlow

Explore PyTorch's latest advancements in AI research and production, including distributed training, model optimization, and deployment using MLFlow, with insights on scaling and efficiency.

• YouTube
• 44 minutes
• On-Demand
• Free Video

Databricks

Object Detection with Transformers - From Training to Deployment

Explore cutting-edge object detection using transformers, from fundamental concepts to advanced techniques. Learn scalable training with Determined AI and deployment using MLflow.

• YouTube
• 32 minutes
• On-Demand
• Free Video

Databricks

Automated Background Removal Using PyTorch - Wehkamp's Image Processing Pipeline

Discover an automated pipeline for efficient background removal in product images using PyTorch and machine learning, enhancing visual experiences for e-commerce customers.

• YouTube
• 23 minutes
• On-Demand
• Free Video