PDC4S:\2018-2\Deep Learning Crash Course

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NameSizeDate Modified
01 - Why this course.mp492,405 KB3/29/2019 8:00 PM
02 - Why Machine Learning.mp499,941 KB3/29/2019 8:00 PM
03 - Our problem in the TensorFlow Playground.mp424,727 KB3/29/2019 8:00 PM
04 - How does a neuron work.mp475,946 KB3/29/2019 8:00 PM
05 - Drawing Decision Boundaries with a single neuron.mp422,465 KB3/29/2019 8:00 PM
06 - Activation Functions.mp442,907 KB3/29/2019 8:00 PM
07 - Fully Connected Feed Forward Networks.mp426,136 KB3/29/2019 7:59 PM
08 - How does a network learn.mp442,417 KB3/29/2019 8:00 PM
09 - Finding the sweet spot.mp416,699 KB3/29/2019 8:00 PM
10 - Summary.mp412,288 KB3/29/2019 8:00 PM
11 - Python Notebooks on Colab.mp431,203 KB3/29/2019 8:00 PM
12 - Getting to know our data.mp430,938 KB3/29/2019 7:59 PM
13 - Our first network with TensorFlow and the Keras API.mp454,701 KB3/29/2019 8:00 PM
14 - Evaluating our model.mp454,280 KB3/29/2019 8:00 PM
15 - Training a network with TensorFlow and the Keras API.mp460,934 KB3/29/2019 8:00 PM
16 - Making our model more general.mp429,803 KB3/29/2019 8:00 PM
17 - Summing up and saving our final model.mp428,331 KB3/29/2019 8:00 PM
18 - Converting the Keras model for tensorflow.js.mp420,278 KB3/29/2019 8:00 PM
19 - Gluing together our JavaScript application.mp418,550 KB3/29/2019 8:00 PM
20 - Alternative - Hosting your model on Google Cloud ML.mp472,726 KB3/29/2019 8:00 PM
21 - Alternative - Running on a dedicated Linux server.mp413,374 KB3/29/2019 8:00 PM
22 - Summary.mp417,892 KB3/29/2019 8:00 PM
deep-learning-crash-course-notebooks-master.zip.XML5,714 KB3/29/2019 7:59 PM