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6 easy pieces on what you need to know for TensorFlow from the ground up (tensors, variables, and gradients without using high level APIs). <\/p>\n\n\n\n
This talk is designed for those that know the basics of Machine Learning but need an overview on the fundamentals of TensorFlow. <\/p>\n\n\n\n
Chapters: <\/p>\n\n\n\n
0:00<\/a> – Intro and outline <\/p>\n\n\n\n 2:12<\/a> – Tensors <\/p>\n\n\n\n 6:08<\/a> – Variables <\/p>\n\n\n\n 9:19<\/a> – Gradient tape <\/p>\n\n\n\n 13:57<\/a> – Modules <\/p>\n\n\n\n 17:43<\/a> – Training loops <\/p>\n\n\n\n 21:52<\/a> – tf.function <\/p>\n\n\n\n 28:53<\/a> – Conclusion <\/p>\n\n\n\n <\/p>\n\n\n\n Resources: <\/p>\n\n\n\n This talk is based on the guides on tensorflow.org See them all (with executable code on Google Colab!) <\/p>\n\n\n\n \u2192 https:\/\/goo.gle\/3ije3k5<\/a> <\/p>\n\n\n\n Tensors <\/p>\n\n\n\n \u2192 https:\/\/goo.gle\/34UqV8m<\/a> <\/p>\n\n\n\n Variables <\/p>\n\n\n\n \u2192 https:\/\/goo.gle\/3v2Pvyh<\/a> <\/p>\n\n\n\n Introduction to gradients and automatic differentiation <\/p>\n\n\n\n \u2192 https:\/\/goo.gle\/3sFVybo<\/a> <\/p>\n\n\n\n Introduction to graphs <\/p>\n\n\n\n \u2192 https:\/\/goo.gle\/3w1cGdE<\/a> <\/p>\n\n\n\n Introduction to modules, layers, and models <\/p>\n\n\n\n \u2192 https:\/\/goo.gle\/3v0mSC1<\/a> <\/p>\n\n\n\n Basic training loops <\/p>\n\n\n\n