TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

Overview

This course aims to teach learners how to use TensorFlow 2.0 for machine learning and artificial intelligence. By completing the course, students will gain knowledge of core learning algorithms, neural networks, computer vision, natural language processing, and reinforcement learning. The course includes in-depth explanations and coding examples to equip learners with the skills needed to apply these techniques to their own datasets and unique problems. The course utilizes Google Colaboratory Notebooks for practical exercises. The intended audience for this course is Python programmers looking to enhance their skills in machine learning and artificial intelligence.

Syllabus

) Module 1: Machine Learning Fundamentals .
) Module 2: Introduction to TensorFlow.
) Module 3: Core Learning Algorithms.
) Module 4: Neural Networks with TensorFlow.
) Module 5: Deep Computer Vision - Convolutional Neural Networks.
) Module 6: Natural Language Processing with RNNs.
) Module 7: Reinforcement Learning with Q-Learning.
) Module 8: Conclusion and Next Steps.