Introduction to TensorFlow for AI, Machine Learning & Deep Learning

DeepLearning.ai

Gain hands-on experience in building neural networks, training them for computer vision, and understanding the use of convolutions to improve model performance.

Video CoursesArtificial IntelligenceNeural NetworksTensorFlow

Introduction

This course provides an introduction to TensorFlow, a popular open-source machine learning framework, and covers the fundamentals of artificial intelligence, machine learning, and deep learning. Learners will gain hands-on experience in building basic neural networks, training them for computer vision applications, and understanding the use of convolutions to improve model performance.

Highlights

  • Learn best practices for using TensorFlow
  • Build a basic neural network in TensorFlow
  • Train a neural network for a computer vision application
  • Understand how to use convolutions to improve your neural network

Recommendation

This course is recommended for anyone interested in gaining a foundational understanding of TensorFlow and its applications in artificial intelligence, machine learning, and deep learning. It is suitable for beginners as well as those with some prior experience in these fields.

How GetVM Works

Learn by Doing from Your Browser Sidebar

Access from Browser Sidebar

Access from Browser Sidebar

Simply install the browser extension and click to launch GetVM directly from your sidebar.

Select Your Playground

Select Your Playground

Choose your OS, IDE, or app from our playground library and launch it instantly.

Learn and Practice Side-by-Side

Learn and Practice Side-by-Side

Practice within the VM while following tutorials or videos side-by-side. Save your work with Pro for easy continuity.

Explore Similar Hands-on Tutorials

A Selective Overview of Deep Learning 3
Technical TutorialsDeep LearningMachine LearningNeural Networks
Comprehensive overview of key concepts and recent advancements in deep learning, covering neural network models, training techniques, and theoretical foundations.
Free and Open Machine Learning 28
Technical TutorialsMachine LearningPythonPyTorchTensorFlow
Discover the power of open-source machine learning with this comprehensive guide, covering key concepts, architecture, and FOSS tools for practical business applications.
The Little Book of Deep Learning 22
Technical TutorialsMachine LearningNeural Networks
A concise and informative guide covering key topics in deep learning, machine learning, and neural networks. Explore foundations, model architectures, and practical applications.
DALL·E 2 Prompt Book | AI-Powered Image Generation, Creative Writing 6
Technical TutorialsArtificial Intelligence
Explore the innovative AI technology of DALL·E 2 that generates realistic images from textual descriptions, offering insights into creative writing and visual artistry.
Guide to Prompt Engineering 6
Technical TutorialsArtificial IntelligenceNatural Language Processing
Comprehensive course on prompt engineering for AI applications like ChatGPT. Covers fundamentals, advanced techniques, and practical strategies to master the art of effective prompting.
Prompt Engineering Guide | Comprehensive Resource for Engineering, Programming & Development 8
Technical TutorialsArtificial Intelligence
Explore the Prompt Engineering Guide by DAIR.AI, a comprehensive resource covering prompt engineering, large language models, and practical guidance for building effective applications.
MIT's Artificial Intelligence Course | Machine Learning, Computer Science 6
Video CoursesArtificial IntelligenceComputer ScienceMachine Learning
Comprehensive introduction to fundamental AI concepts, including knowledge representation, problem solving, and learning. Develop intelligent systems and explore the role of AI in understanding human intelligence.
Building a simple Generative Adversarial Network (GAN) using Tensorflow 7
Technical TutorialsPythonTensorFlow
Hands-on introduction to building a simple Generative Adversarial Network (GAN) using TensorFlow. Understand the core concept, implement the model, and visualize the process.
Tensorflow for Deep Learning Research | Stanford University 18
University CoursesDeep LearningMachine LearningTensorFlow
Learn the fundamentals of TensorFlow for deep learning research. Build models for tasks like word embeddings, translation, and optical character recognition.