If you find this useful: 1. Retweet and follow me @Sumanth_077 for more content on Python, Data Science, and Machine Learning 2. I go deeper into these topics, also interview data professionals on my YT Channel. Join 1.6k+ others and subscribe below! https://
youtube.com/channel/UCGtqG
YDxlzfgOnugpOcGxkA
…
@sumanth_077
-
Follow for Python, Data Science, and Machine Learning Content
By
–
-
MIT’s Introduction to Deep Learning: Complete Overview
By
–
5. MIT's Introduction to Deep Learning This Course will give you a complete idea of Deep Learning, Computer vision and Natural Language Processing
-
Linear Algebra Fundamentals for Machine Learning Overview
By
–
4. Linear Algebra Get an overview of the important and basic concepts of Linear Algebra required for Machine Learning https://
ocw.mit.edu/courses/res-18
-010-a-2020-vision-of-linear-algebra-spring-2020/
… -
Statistics for Applications: Essential Concepts for Data Science
By
–
3. Statistics for Applications Statistics plays a crucial role in Data Science. Learn the important stats concepts and their practical use cases. https://
ocw.mit.edu/courses/18-650
-statistics-for-applications-fall-2016
… -
Introduction to Data Science and Machine Learning Fundamentals
By
–
2. Introduction To Data Science You'll learn about all the fundamental concepts of Data Science and Machine Learning. https://
ocw.mit.edu/courses/6-0002
-introduction-to-computational-thinking-and-data-science-fall-2016/
… -
JAX NumPy Level Comparison with PyTorch Framework
By
–
Thank you. JAX works at the NumPy level. So we can't actually compare it with Pytorch which is a framework with high-level APIs. Regarding the advantages, have already mentioned them in the thread.
-
Daily Python Data Science Machine Learning Tutorials Wrap
By
–
That's a wrap! Every day, I share tutorials around Python, Data Science & Machine Learning. You can follow me → @Sumanth_077 Like/RT the first tweet to support my work and help this reach more people
-
XLA and Automatic Parallelization in JAX for Computation Speed
By
–
XLA & Automatic Parallelization It also supports XLA or Accelerated Linear Algebra, which is an optimizing compiler, designed specifically to increase the computation speed. And also supports Parallelization and can be done using "pmap()" https://
jax.readthedocs.io/en/latest/note
books/quickstart.html
… -
Automatic Vectorization with JAX vmap Function
By
–
Automatic Vectorization Vectorization helps faster code execution and Jax has an inbuilt function to do the same And can be done with using "vmap()" function Here are the detailed use cases and implementation of Vectorization. http://
jax.readthedocs.io/en/latest/_aut
osummary/jax.vmap.html#jax.vmap
…