This TensorFlow beginner course provides a complete introduction to deep learning using one of the most popular machine learning frameworks. It is designed for beginners who want to understand how neural networks work and how to build real AI models using TensorFlow.
The course starts with installation and setup, ensuring you have a proper development environment for building deep learning applications. You will then learn the fundamentals of tensors, which are the core data structures used in TensorFlow for numerical computation and model training.
A major part of the course focuses on building your first neural network, including training, evaluation, and prediction. You will understand how models learn from data and how performance is measured.
The course also includes practical machine learning projects such as linear regression and image classification using convolutional neural networks (CNNs). These projects help you apply theoretical knowledge to real-world problems.
You will also learn how to save and load trained models, use the Functional API for building complex architectures, and work on multi-output models for advanced use cases.
Additionally, the course covers transfer learning and real-world classification projects such as identifying Lego Star Wars minifigures, helping you understand how pre-trained models can be reused effectively.
By the end of this course, you will have a strong foundation in TensorFlow and deep learning, enabling you to build and deploy your own AI models.
