Master Machine Learning from scratch using Javascript and TensorflowJS with hands-on projects.
InstructorStephen Grider
Instruction covers the mechanics of algorithms like K-Nearest Neighbor and gradient descent, including MSE calculations and matrix operations.
The curriculum includes specific techniques for handling large datasets and managing memory via the garbage collector and TensorFlow's 'tidy' function.
Editorial course preview
These 3 complementary views highlight concrete, legible examples from the course presentation.
A graphic displaying three icons representing code, data structures, and flowcharts, with the text 'MACHINE LEARNING TECHNIQUES' at the bottom.
This graphic illustrates the course structure by pairing a step-by-step guide on a yellow panel with a practical coding example displayed on a laptop screen.
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A signal from 2024 suggests the TensorFlow version used may be outdated, potentially causing unexpected function behavior; while the course was updated in 2026, this update does not guarantee a correction.
A signal from 2024 indicates that some examples lack practical, real-world applicability for professional scenarios; the 2026 update label does not confirm these have been addressed.
The course aligns with the goal of teaching machine learning to JavaScript developers, though currency concerns exist.