Deep Learning using TensorFlow

IBM Deep Learning using TensorFlow is a program that equips participants with the ability to apply TensorFlow for deep learning tasks. Here are the key components covered in this program:

1. Foundational TensorFlow Concepts:
   • Participants learn essential TensorFlow concepts, including main functions, operations, and execution pipelines.
   • They understand how TensorFlow can be used for tasks such as curve fitting, regression, classification, and error function minimization.
2. Deep Architectures:
   • The program covers different types of deep architectures, including Convolutional Networks, Recurrent Networks, and Autoencoders.
   • Participants explore how to apply TensorFlow for backpropagation to tune weights and biases during neural network training.

By completing this program, participants demonstrate their ability to work effectively with TensorFlow for deep learning tasks, making them valuable contributors to AI-driven projects. 🌟🔍

For more details, you can visit the IBM Training page¹.