TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
Learn how to use TensorFlow 2.0 in this full tutorial course for beginners. This course is designed for Python programmers looking to enhance their knowledge and skills in machine learning and artificial intelligence.
Throughout the 8 modules in this course you will learn about fundamental concepts and methods in ML & AI like core learning algorithms, deep learning with neural networks, computer vision with convolutional neural networks, natural language processing with recurrent neural networks, and reinforcement learning.
Each of these modules include in-depth explanations and a variety of different coding examples. After completing this course you will have a thorough knowledge of the core techniques in machine learning and AI and have the skills necessary to apply these techniques to your own data-sets and unique problems.
βοΈ Google Colaboratory Notebooks βοΈ
π Module 2: Introduction to TensorFlow - https://colab.research.google.com/drive/1F_EWVKa8rbMXi3_fG0w7AtcscFq7Hi7B#forceEdit=true&sandboxMode=true
π Module 3: Core Learning Algorithms - https://colab.research.google.com/drive/15Cyy2H7nT40sGR7TBN5wBvgTd57mVKay#forceEdit=true&sandboxMode=true
π Module 4: Neural Networks with TensorFlow - https://colab.research.google.com/drive/1m2cg3D1x3j5vrFc-Cu0gMvc48gWyCOuG#forceEdit=true&sandboxMode=true
π Module 5: Deep Computer Vision - https://colab.research.google.com/drive/1ZZXnCjFEOkp_KdNcNabd14yok0BAIuwS#forceEdit=true&sandboxMode=true
π Module 6: Natural Language Processing with RNNs - https://colab.research.google.com/drive/1ysEKrw_LE2jMndo1snrZUh5w87LQsCxk#forceEdit=true&sandboxMode=true
π Module 7: Reinforcement Learning - https://colab.research.google.com/drive/1IlrlS3bB8t1Gd5Pogol4MIwUxlAjhWOQ#forceEdit=true&sandboxMode=true
βοΈ Course Contents βοΈ
β¨οΈ (00:03:25) Module 1: Machine Learning Fundamentals
β¨οΈ (00:30:08) Module 2: Introduction to TensorFlow
β¨οΈ (01:00:00) Module 3: Core Learning Algorithms
β¨οΈ (02:45:39) Module 4: Neural Networks with TensorFlow
β¨οΈ (03:43:10) Module 5: Deep Computer Vision - Convolutional Neural Networks
β¨οΈ (04:40:44) Module 6: Natural Language Processing with RNNs
β¨οΈ (06:08:00) Module 7: Reinforcement Learning with Q-Learning
β¨οΈ (06:48:24) Module 8: Conclusion and Next Steps
βοΈ About the Author βοΈ
The author of this course is Tim Ruscica, otherwise known as βTech With Timβ from his educational programming YouTube channel. Tim has a passion for teaching and loves to teach about the world of machine learning and artificial intelligence. Learn more about Tim from the links below:
π YouTube: https://www.youtube.com/channel/UC4JX40jDee_tINbkjycV4Sg
π LinkedIn: https://www.linkedin.com/in/tim-ruscica/
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