TensorFlow - Mastering Deep Learning for Intelligent Innovation

Overview

🕮 Off the shelf (OTS)

This course is designed for data scientists, machine learning engineers, software developers, and analysts who are looking to build and deploy machine learning models using TensorFlow. It is ideal for professionals aiming to develop a deep understanding of neural networks, deep learning concepts, and practical TensorFlow implementation.

Participants should have a working knowledge of Python programming and a basic understanding of machine learning principles and statistics.

The TensorFlow Training Course provides a comprehensive introduction to developing and deploying machine learning models using Google’s open-source TensorFlow framework. The course covers key aspects of building neural networks, working with high-level APIs such as Keras, and optimizing model performance. Through hands-on exercises, participants will gain practical experience with TensorFlow tools and workflows, enabling them to construct and train scalable models for a range of real-world applications.

Key Topics Covered:
• Introduction to machine learning and deep learning fundamentals
• TensorFlow architecture and computational graphs
• Building and training neural networks using TensorFlow and Keras
• Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs)
• Data input pipelines and preprocessing techniques
• Model evaluation, tuning, and deployment strategies
• TensorBoard for monitoring and visualization
• Best practices for scalable and efficient model development

The course is delivered over three days and includes hands-on exercises to reinforce learning.