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视频-2 - 7 - gradientdescentforlinearregression (6 min).mkv 2017-09-07
视频-2 - 8 - what_'s next (6 min).mkv 2017-09-07
视频-6 - 1 - classification (8 min).mkv 2017-09-07
视频-4 - 1 - multiple features (8 min).mkv 2017-09-07
视频-8 - 2 - neurons and the brain (8 min).mkv 2017-09-07
视频-5 - 2 - moving data around (16 min).mkv 2017-09-07
视频-3 - 1 - matrices and vectors (9 min).mkv 2017-09-07
视频-9 - 1 - cost function (7 min).mkv 2017-09-07
视频-2 - 2 - cost function (8 min).mkv 2017-09-07
视频-5 - 6 - vectorization (14 min).mkv 2017-09-07
视频-9 - 8 - autonomous driving (7 min).mkv 2017-09-07
视频-9 - 7 - putting it together (14 min).mkv 2017-09-07
视频-8 - 7 - multiclass classification (4 min).mkv 2017-09-07
视频-6 - 2 - hypothesis representation (7 min).mkv 2017-09-07
视频-2 - 1 - model representation (8 min).mkv 2017-09-07
视频-9 - 6 - random initialization (7 min).mkv 2017-09-07
视频-8 - 5 - examples and intuitions i (7 min).mkv 2017-09-07
视频-3 - 6 - inverse and transpose (11 min).mkv 2017-09-07
视频-5 - 1 - basic operations (14 min).mkv 2017-09-07
视频-19 - 1 - summary and thank you (5 min).mkv 2017-09-07
视频-13 - 3 - optimization objective (7 min).mkv 2017-09-07
视频-6 - 4 - cost function (11 min).mkv 2017-09-07
视频-9 - 3 - backpropagation intuition (13 min).mkv 2017-09-07
视频-3 - 2 - addition and scalar multiplication (7 min).mkv 2017-09-07
视频-2 - 5 - gradient descent (11 min).mkv 2017-09-07
视频-8 - 3 - model representation i (12 min).mkv 2017-09-07
视频-9 - 2 - backpropagation algorithm (12 min).mkv 2017-09-07
视频-4 - 6 - normal equation (16 min).mkv 2017-09-07
视频-7 - 4 - regularized logistic regression (9 min).mkv 2017-09-07
视频-12 - 6 - using an svm (21 min).mkv 2017-09-07

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