Learn to use Python for Deep Learning with Google's latest Tensorflow 2 library and Keras!
InstructorJose Portilla
Coupon
The curriculum spans multiple neural network types including Convolutional Neural Networks, Recurrent Neural Networks, AutoEncoders, and GANs.
Instruction includes dedicated modules for NumPy, Pandas, and data visualization to establish prerequisite technical skills.
Editorial course preview
These 3 complementary views highlight concrete, legible examples from the course presentation.
This screenshot displays the TensorBoard interface used to visualize model training metrics, specifically showing histograms for dense layer parameters.
This visual summary outlines the course materials provided to students, combining HD video lectures with code templates and explanatory slide decks.
This illustration highlights that each section includes assessments and exercises to practice your skills, ensuring active engagement beyond just watching videos.
Significant deprecations in TensorFlow and Keras methods, alongside potential issues with modern NumPy versions, may require manual workarounds.
Significant deprecations in TensorFlow and Keras methods, alongside potential issues with modern NumPy versions, may require manual workarounds.
The curriculum aligns with the target of Python developers, though deployment may require web development knowledge.