Tensorboard Courses and Certifications

Microcredential

TensorFlow: Data and Deployment

Explore advanced TensorFlow deployment scenarios across browsers, mobile devices, and various platforms. Learn data pipeline management, model retraining, and privacy-preserving techniques for real-world AI applications.

• Coursera
• 17 weeks, 3 hours a week
• On-Demand
• Paid Course
• 4 courses

Advanced Deployment Scenarios with TensorFlow

507 ratings at Coursera

Explore advanced deployment scenarios using TensorFlow Serving, TensorFlow Hub, TensorBoard, and federated learning to effectively bring machine learning models into real-world applications.

• Coursera
• 12 hours 58 minutes
• On-Demand
• Free Online Course (Audit)

Introduction to TensorFlow in R

Learn how to use TensorFlow, a state-of-the-art machine learning framework that specializes in the ability to develop deep learning neural networks.

• DataCamp
• 4 hours
• On-Demand
• Free Trial Available

Intro to Deep Learning project in TensorFlow 2.x and Python

78 ratings at Udemy

Advanced implementation of regression modelling techniques like lasso regression in TensorFlow

• Udemy
• 5 hours 43 minutes
• On-Demand
• Paid Course

Neural Network Programming - Deep Learning with PyTorch

1 review

Learn to build and train neural networks using PyTorch, covering tensor operations, CNN architecture, data preparation, training loops, and performance optimization techniques for deep learning projects.

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

Building and Deploying Deep Learning Applications with TensorFlow

516 ratings at LinkedIn Learning

Discover how to install TensorFlow and use it to create, train, and deploy a machine learning model.

• LinkedIn Learning
• 1 hour 47 minutes
• On-Demand
• Free Trial Available

TensorFlow: Working with Images

87 ratings at LinkedIn Learning

Learn the ins and outs of working with images in TensorFlow 2.0

• LinkedIn Learning
• 40 minutes
• On-Demand
• Free Trial Available

Learning Vertex AI: MLOps with Google Cloud

71 ratings at LinkedIn Learning

Learn how to train, deploy, and manage machine learning models using built-in tools in Vertex AI.

• LinkedIn Learning
• 1 hour 39 minutes
• On-Demand
• Free Trial Available

Building Deep Learning Applications with Keras 2.0

50 ratings at LinkedIn Learning

Get a thorough introduction to Keras, a versatile deep learning framework, and learn how to build, deploy, and monitor robust deep learning models.

• LinkedIn Learning
• 1 hour 51 minutes
• On-Demand
• Free Trial Available

Code Monkey

How to Use Machine Learning AI in Unity - ML-Agents

Unlock the power of Machine Learning AI in Unity with ML-Agents. Learn installation, agent creation, training, and visualization to enhance your game development skills.

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

TensorFlow

Inside TensorFlow - TF Debugging

Explore TensorFlow debugging techniques for TF 2 and TF 1, covering tensor value printing, device placement, graph visualization, and step debugging in Keras models.

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

TensorFlow

Inside TensorFlow - Summaries and TensorBoard

Explore TensorBoard and tf.summary API for data visualization in TensorFlow. Learn about API changes, log directories, event files, and best practices from a TensorFlow engineer.

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

Intro to PyTorch Tutorial - Building Fashion Recognizer

Learn to build a fashion recognizer using PyTorch in this hands-on tutorial. Covers core functionality, network architecture, loss functions, optimizers, and TensorBoard integration for effective model training.

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

Devoxx

Machine Learning Using Kubeflow and Kubernetes

Explore machine learning workflows on Kubernetes using Kubeflow, covering deployment, training, inference, and advanced features like hyperparameter tuning and automated pipelines.

• YouTube
• 51 minutes
• On-Demand
• Conference Talk

deeplizard

Batch Normalization in PyTorch - Adding Normalization to Convolutional Neural Network Layers

Learn to implement batch normalization in convolutional neural networks using PyTorch. Explore the benefits, create and compare networks, and optimize performance through hands-on coding and practical examples.

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