Learning JAX
Focused View
Janani Ravi
2:23:17
141 View
01 - Prerequisites.mp4
00:55
02 - What is JAX.mp4
03:28
03 - Why use JAX.mp4
05:29
04 - Choosing JAX.mp4
02:26
05 - JAX vs. TensorFlow vs. PyTorch.mp4
04:09
06 - Getting set up with Colab.mp4
02:05
01 - JAX arrays.mp4
04:30
02 - JAX arrays and NumPy arrays Similarities.mp4
04:49
03 - JAX arrays and NumPy arrays Differences.mp4
02:54
04 - Asynchronous dispatch and JAX array speed up.mp4
02:59
01 - Composable function transformations.mp4
03:18
02 - JIT and pure functions.mp4
05:22
03 - Using JIT.mp4
03:38
04 - Tracer objects in JIT.mp4
05:06
05 - Impure functions and JIT IO streams.mp4
01:45
06 - Impure functions and JIT Global state.mp4
03:33
07 - Impure functions and JIT Iterators.mp4
02:56
08 - Jaxprs.mp4
02:36
09 - Control flow statements and JIT.mp4
02:24
10 - Static arguments in jitted functions.mp4
03:34
11 - Lambdas and JIT.mp4
01:52
01 - Understanding vectorization and parallelization.mp4
04:19
02 - Automatic vectorization.mp4
04:50
03 - Comparing naive and manual batching with automatic vectorization.mp4
06:06
01 - Understanding gradient computation.mp4
02:56
02 - Gradient computation.mp4
03:00
03 - Higher order gradients.mp4
03:16
04 - Jacobians and Hessians.mp4
03:20
01 - Understanding pytrees.mp4
02:59
02 - Simple pytrees.mp4
05:40
03 - Operations on pytrees.mp4
03:17
04 - Pytree containers.mp4
01:40
05 - Custom containers as pytrees.mp4
03:43
01 - Regression using a single neuron Loading and preprocessing data.mp4
04:02
02 - Regression using a single neuron Helper functions.mp4
03:07
03 - Regression using a single neuron Training and evaluating a model.mp4
02:23
04 - Regression using a neural network Helper functions.mp4
05:09
05 - Regression using a neural network Training a model and visualizing results.mp4
02:44
06 - Classification using neural network Loading and preprocessing data.mp4
03:57
07 - Classification using neural network Training and evaluating model.mp4
04:50
01 - Summary and next steps.mp4
02:11
Description
In this course, instructor Janani Ravi gives you an in-depth look at JAX, a new experimental Python library designed for high performance, scientific computing and machine learning. Janani takes you through all aspects of JAX and what it is capable of, including: just-in-time compilation; automatic vectorization and automatic parallelization; computing gradients; performing transformations on pytrees; training simple neural networks; and more.
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Janani Ravi
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Linkedin Learning
View courses Linkedin LearningLinkedIn Learning is an American online learning provider. It provides video courses taught by industry experts in software, creative, and business skills. It is a subsidiary of LinkedIn. All the courses on LinkedIn fall into four categories: Business, Creative, Technology and Certifications.
It was founded in 1995 by Lynda Weinman as Lynda.com before being acquired by LinkedIn in 2015. Microsoft acquired LinkedIn in December 2016.
- language english
- Training sessions 41
- duration 2:23:17
- Release Date 2022/12/11
