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TensorFlow 2.0 Complete Course – Python Neural Networks for Beginners Tutorial



freeCodeCamp.org

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.

⭐️ Google Colaboratory Notebooks ⭐️

📕 Module 2: Introduction to TensorFlow – https://colab.research.google.com/drive/1F_EWVKa8rbMXi3_fG0w7AtcscFq7Hi7B#forceEdit=true&sandboxMode=true
📗 Module 3: Core Learning Algorithms – https://colab.research.google.com/drive/15Cyy2H7nT40sGR7TBN5wBvgTd57mVKay#forceEdit=true&sandboxMode=true
📘 Module 4: Neural Networks with TensorFlow – https://colab.research.google.com/drive/1m2cg3D1x3j5vrFc-Cu0gMvc48gWyCOuG#forceEdit=true&sandboxMode=true
📙 Module 5: Deep Computer Vision – https://colab.research.google.com/drive/1ZZXnCjFEOkp_KdNcNabd14yok0BAIuwS#forceEdit=true&sandboxMode=true
📔 Module 6: Natural Language Processing with RNNs – https://colab.research.google.com/drive/1ysEKrw_LE2jMndo1snrZUh5w87LQsCxk#forceEdit=true&sandboxMode=true
📒 Module 7: Reinforcement Learning – https://colab.research.google.com/drive/1IlrlS3bB8t1Gd5Pogol4MIwUxlAjhWOQ#forceEdit=true&sandboxMode=true

⭐️ Course Contents ⭐️

⌨️ Module 1: Machine Learning Fundamentals (00:03:25)
⌨️ Module 2: Introduction to TensorFlow (00:30:08)
⌨️ Module 3: Core Learning Algorithms (01:00:00)
⌨️ Module 4: Neural Networks with TensorFlow (02:45:39)
⌨️ Module 5: Deep Computer Vision – Convolutional Neural Networks (03:43:10)
⌨️ Module 6: Natural Language Processing with RNNs (04:40:44)
⌨️ Module 7: Reinforcement Learning with Q-Learning (06:08:00)
⌨️ Module 8: Conclusion and Next Steps (06:48:24)

⭐️ About the Author ⭐️

The author of this course is Tim Ruscica, otherwise known as “Tech With Tim” 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:
🔗 YouTube: https://www.youtube.com/channel/UC4JX40jDee_tINbkjycV4Sg
🔗 LinkedIn: https://www.linkedin.com/in/tim-ruscica/

Learn to code for free and get a developer job: https://www.freecodecamp.org

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25 thoughts on “TensorFlow 2.0 Complete Course – Python Neural Networks for Beginners Tutorial
  1. for module 3 I am getting {'accuracy': 0.625, 'accuracy_baseline': 0.625, 'auc': 0.5} everytime what I have done wrong here can anyone explain please help!

  2. I have gone through complete lecture and i have no idea. I seek to come here after 6 months and write down list of projects i did.I am starting from scratch. I am mechanical engineer.

  3. ⌨️ Module 1: Machine Learning Fundamentals (00:03:25)
    ⌨️ Module 2: Introduction to TensorFlow (00:30:08)
    ⌨️ Module 3: Core Learning Algorithms (01:00:00)
    ⌨️ Module 4: Neural Networks with TensorFlow (02:45:39)
    ⌨️ Module 5: Deep Computer Vision – Convolutional Neural Networks (03:43:10)
    ⌨️ Module 6: Natural Language Processing with RNNs (04:40:44)
    ⌨️ Module 7: Reinforcement Learning with Q-Learning (06:08:00)
    ⌨️ Module 8: Conclusion and Next Steps (06:48:24)

  4. Tim got 80% accuracy on the flowers classification while I am getting 95% with the same code. Same number of steps and same GNNClassifier. Is someone getting the same thing?

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