Learn TensorFlow by Google. Become an AI, Machine Learning, and Deep Learning expert!
InstructorAndrei Neagoie
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Editorial course preview
These 2 complementary views highlight concrete, legible examples from the course presentation.
A dark-themed code editor showing Python source code for a TensorFlow Keras model, including layer definitions and compilation settings.
A vehicle interior view showing a driver, a central navigation screen, and a side panel with three camera feeds displaying object detection boxes and labels.
The curriculum features distinct projects targeting computer vision, NLP, and time series forecasting to demonstrate practical application.
Transfer learning is broken down into logical stages including feature extraction, fine-tuning, and scaling up.
One signal suggests the presence of older code that may not reflect current best practices, despite the update label.
Some signals indicate a lack of simplified definitions and a need for more logical explanations of underlying algorithms.
The curriculum aligns well with the goal of becoming a TensorFlow developer through practical model building.