Silicon Valley Hands On Programming Events

React Programming

There have been some changes post Covid. There has been a transition away from in person meetings and events towards video conferencing and online learning.

One of the basic tasks for data science is to visualize data. Generating matplotlib or ggplot graphs is not a sufficient career skill. Most of the visualizations require some UI skill and it is not unreasonable to assume a Data Scientist or ML engineer should have some of those skills. Before Karpathy ended up at Tesla he wrote large amounts of JS code and was able to build UIs.

Here is a link to a free Github game showing how a github workflow works.
https://profy.dev/project/github-minesweeper

There is also a link to a "React Job Simulator" which is unlike 99% of the small project React courses in that it is much closer to a production build and workflow you will see at a company.

https://www.youtube.com/watch?v=Aw4_pA2alTc

The "React Job Simulator" course starts on 9/25 and is not a free course. It covers a complex codebase for a UI dashboard, includes modern comonents like the tanstack React Query instead of managing axios or fetch requests. Includes testing and storybook component workflows.
None of the Udemy, Coursera or online classes go to this level of detail and effort to provide a React template this close to dev/prod.

Uses nextjs, not CRA.

If we get enough interest we may be able to do a weekly session using this course as a format for practice.

Example of workflow in the course starting 9/25. Local timezone in Germany.

https://www.youtube.com/watch?v=25bRAvRHVPM

There is no physical meetup for this post.

Deep learning is evolving quickly. Important new developments are appearing daily. This group attempts to keep up by reading and discussing current deep learning literature. This meetup uses discussion among the participants to speed understanding of current research results. That requires that some participants read the paper before attending. Anyone is welcome to attend and listen without reading the paper. If nobody reads the paper the meeting will be short.

Papers that we're reading, code that participants generate and other random stuff can be found at github site for the group.

mike-bowles/hdDeepLearningStudy (https://github.com/mike-bowles/hdDeepLearningStudy)

Deep learning is evolving quickly. Important new developments are appearing daily. This group attempts to keep up by reading and discussing current deep learning literature. This meetup uses discussion among the participants to speed understanding of current research results. That requires that some participants read the paper before attending. Anyone is welcome to attend and listen without reading the paper. If nobody reads the paper the meeting will be short.

Papers that we're reading, code that participants generate and other random stuff can be found at github site for the group.

mike-bowles/hdDeepLearningStudy (https://github.com/mike-bowles/hdDeepLearningStudy)