📊 Deep Learning with TensorFlow & Keras

TensorFlow 2.x / Keras 3 end to end — tensors, tf.data pipelines, training loops, CNNs, transfer learning, and deployment to Serving/TFLite.

9-Lesson mini-course — TensorFlow 2.x / Keras 3 end to end — tensors, tf.data pipelines, training loops, CNNs, transfer learning, and deployment to Serving/TFLite.

Like every course on this site, each lesson is a deep, code-first lesson: an intuition-first explainer, a staged code walkthrough explaining the methodology line by line, visuals, and a 🧪 Your task exercise with a hidden solution. Theory lives in the AI & ML Encyclopedia; here you build.

▶ Start Lesson 1   📚 All mini-courses

Syllabus

#	Lesson
Lesson 1	Tensors, Variables & GradientTape
Lesson 2	Keras Models Three Ways: Sequential, Functional, Subclassing
Lesson 3	Feeding the Beast: Input Pipelines with tf.data
Lesson 4	compile/fit, the Callback Zoo, and Rolling Your Own Training Loop
Lesson 5	Classification End to End: From Raw Pixels to a Confusion Matrix
Lesson 6	CNNs in Keras: Convolutions, Pooling, and Augmentation as Layers
Lesson 7	Regularization & Tuning: Making the CNN Behave
Lesson 8	Transfer Learning: Stand on a Million Shoulders
Lesson 9	Saving & Deployment: From .keras to the Edge