android_guides
Kalman-and-Bayesian-Filters-in-Python
android_guides | Kalman-and-Bayesian-Filters-in-Python | |
---|---|---|
4 | 32 | |
28,259 | 15,787 | |
0.0% | - | |
2.1 | 0.0 | |
12 months ago | 3 months ago | |
Jupyter Notebook | ||
MIT License | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
android_guides
-
Simple Android RecyclerView example
I've made a list of items a few times using Android's RecyclerView, but it is a rather complicated process. Going through one of the numerous tutorials online works (this, this, and this are good), but I am looking a bare bones example that I can copy and paste to get up and running quickly. Only the following features are necessary:
-
Dying to understand RecyclerView
When I was learning about RecyclerView I read this article about it: https://github.com/codepath/android_guides/wiki/Using-the-RecyclerView
-
Free 500+ books and learning resources for every programmer.
CodePath Android Cliffnotes
-
Publish Android Library Artifacts to private Amazon S3 Maven repository
https://github.com/codepath/android_guides/wiki/Building-your-own-Android-library#setting-up-a-private-amazon-s3-maven-repository
Kalman-and-Bayesian-Filters-in-Python
-
The Kalman Filter
A fantastic interactive introduction to Kalman filters can be found on the following repo:
https://github.com/rlabbe/Kalman-and-Bayesian-Filters-in-Pyt...
It explains them from first principles and provides the intuitive rationale for them but doesn't shy away from the math when it feels the student should be ready for it.
-
Kalman Filter Explained Simply
No thread on Kalman Filters is complete without a link to this excellent learning resource, a book written as a set of Jupyter notebooks:
https://github.com/rlabbe/Kalman-and-Bayesian-Filters-in-Pyt...
That book mentions alpha-beta filters as sort of a younger sibling to full-blown Kalman filters. I recently had need of something like this at work, and started doing a bunch of reading. Eventually I realized that alpha-beta filters (and the whole Kalman family) is very focused on predicting the near future, whereas what I really needed was just a way to smooth historical data.
So I started reading in that direction, came across "double exponential smoothing" which seemed perfect for my use-case, and as I went into it I realized... it's just the alpha-beta filter again, but now with different names for all the variables :(
I can't help feeling like this entire neighborhood of math rests on a few common fundamental theories, but because different disciplines arrived at the same systems via different approaches, they end up sounding a little different and the commonality is obscured. Something about power series, Euler's number, gradient descent, filters, feedback systems, general system theory... it feels to me like there's a relatively small kernel of intuitive understanding at the heart of all that stuff, which could end up making glorious sense of a lot of mathematics if I could only grasp it.
Somebody help me out, here!
-
Recommendations for undergrad to learn optimal state estimation
This provides an excellent intro that jumps right into code. https://github.com/rlabbe/Kalman-and-Bayesian-Filters-in-Python
-
A Non-Mathematical Introduction to Kalman Filters for Programmers
If you know a bit of Python and you find it sometimes tough to grind through a textbook, take a look here:
https://github.com/rlabbe/Kalman-and-Bayesian-Filters-in-Pyt...
Interactive examples programmed in Jupyter notebooks.
- Looking for a study partner to learn kalman filter
-
Kalman Filter for Beginners
Thank you, very good resource! Timely too, as I am revising this topic.
My work is mostly in python. I found this interactive book using Jupyter that explains Kalman filters from first principles.
https://github.com/rlabbe/Kalman-and-Bayesian-Filters-in-Pyt...
- Starting out with Kalman Filter.
-
want to learn kalman filter
Try this book
-
kalman filter & c++
https://github.com/rlabbe/Kalman-and-Bayesian-Filters-in-Python And on robotics in general
-
Do you use particle/Kalman filters at work?
- Kalman and Bayesian Filters in Python
What are some alternatives?
IOTA-Discord - The IOTA Discord information repository (https://discord.iota.org)
30-days-of-elixir - A walk through the Elixir language in 30 exercises.
Free-Range-VHDL-book - Latex source files of the open-source book FREE RANGE VHDL
clojure-style-guide - A community coding style guide for the Clojure programming language
android-developer-roadmap - Android Developer Roadmap 2020
git-internals-pdf - PDF on Git Internals
papers-we-love - Papers from the computer science community to read and discuss.
kalmanpy - Implementation of Kalman Filter in Python
react-bits - ✨ React patterns, techniques, tips and tricks ✨
android-developer-roadmap - 🗺 The Android Developer Roadmap offers comprehensive learning paths to help you understand Android ecosystems.
elm-architecture-tutorial - How to create modular Elm code that scales nicely with your app