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Machine Learning Intermediate

TensorFlow Introduction

A COMPLETE beginner-to-advanced Deep Learning course. Learn neural networks, CNNs, NLP, and deploying AI apps using TensorFlow.

20 chapters 1h 58m 4.7 (139)
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What you'll learn

  • Introduction to Artificial Intelligence, Deep Learning, and TensorFlow
  • Setting Up Python and TensorFlow Environment
  • Python Basics for Deep Learning
  • NumPy, Pandas, and Data Handling
  • Understanding Neural Networks
  • TensorFlow Basics and Tensors
  • Building Your First Neural Network
  • Activation Functions and Loss Functions

Course content

20 chapters · 1h 58m
  1. 1 Introduction to Artificial Intelligence, Deep Learning, and TensorFlow 7 min
  2. 2 Setting Up Python and TensorFlow Environment 6 min
  3. 3 Python Basics for Deep Learning 5 min
  4. 4 NumPy, Pandas, and Data Handling 5 min
  5. 5 Understanding Neural Networks 6 min
  6. 6 TensorFlow Basics and Tensors 6 min
  7. 7 Building Your First Neural Network 6 min
  8. 8 Activation Functions and Loss Functions 6 min
  9. 9 Training and Evaluating Models 6 min
  10. 10 Working with TensorFlow Keras API 6 min
  11. 11 Image Classification with CNNs 6 min
  12. 12 Transfer Learning in TensorFlow 6 min
  13. 13 Natural Language Processing Basics 6 min
  14. 14 Recurrent Neural Networks (RNN) 6 min
  15. 15 LSTM and Sequence Models 6 min
  16. 16 Saving, Loading, and Deploying Models 6 min
  17. 17 TensorFlow Data Pipelines 6 min
  18. 18 Hyperparameter Tuning and Optimization 6 min
  19. 19 TensorFlow Best Practices and Performance Optimization 6 min
  20. 20 Final Project - Build Real-World AI Applications 5 min