Top 23 Jupyter Notebook Jupyter Projects
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homemade-machine-learning
🤖 Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained
Project mention: Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained | reddit.com/r/MachineLearning | 2021-10-27 -
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Scout APM
Less time debugging, more time building. Scout APM allows you to find and fix performance issues with no hassle. Now with error monitoring and external services monitoring, Scout is a developer's best friend when it comes to application development.
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Project mention: How to use Jupyter notebooks in a conda environment? | reddit.com/r/codehunter | 2022-05-09
As it seems, this is not quite straight forward and manyusers have similar troubles.
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Project mention: Learn data science step by step in 6 months😉 | reddit.com/r/Datewithdata | 2022-05-03
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Project mention: Best resource to learn Python for Data Science? | reddit.com/r/learnpython | 2022-05-12
I've worked at a data engineer with data scientists and that is why I'm a fan of nbdev. It gives you the ability of coding in your jupyter notebook though have all all the conforts of softwhere dev. For example github actions (or gitlab pipelines) that will help improve you create notebooks that are ready to collaborate. nbdev also helps package your application into a python package where you can upload to pypi or an private repository and pip install it from there which is great for going from experimenting with data in jupyter to production.
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Project mention: [D] What do you use to make your blog/personal websites? | reddit.com/r/MachineLearning | 2022-04-17
I use FastPages by fastai community: https://fastpages.fast.ai/ It's similar to Markdown in terms of writing the blog and you can even convert your Jupyter Notebook to a blog page directly.
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Yes it surprised me there was so much discussion of jupyter notebooks as if they only support Python but there is great support for all kinds of languages including very statically typed ones (Scala, etc).
I do lots of ML in Groovy using beakerx [0] which is pretty much the last thing anybody would expect but it works great.
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SonarQube
Static code analysis for 29 languages.. Your projects are multi-language. So is SonarQube analysis. Find Bugs, Vulnerabilities, Security Hotspots, and Code Smells so you can release quality code every time. Get started analyzing your projects today for free.
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Project mention: All-in-One Docker Based IDE for Data Science and ML | news.ycombinator.com | 2021-09-24
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Project mention: Machine Learning and Factor Based Portfolio Optimization | reddit.com/r/mltraders | 2022-05-23
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Interactive Parallel Computing with IPython
IPython Parallel: Interactive Parallel Computing in Python
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pytorch-GAT
My implementation of the original GAT paper (Veličković et al.). I've additionally included the playground.py file for visualizing the Cora dataset, GAT embeddings, an attention mechanism, and entropy histograms. I've supported both Cora (transductive) and PPI (inductive) examples!
Project mention: Open-source Graph Attention Network (GAT) project with transductive + inductive Jupiter notebooks ! | reddit.com/r/u_faiqnurhakim1234 | 2022-02-13 -
Project mention: How can I get rid of R in my web programming? | reddit.com/r/learnpython | 2022-03-07
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Project mention: JP Morgan & Chase free python course (r/finance) | reddit.com/r/algoprojects | 2021-09-14
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reinforcement_learning_course_materials
Lecture notes, tutorial tasks including solutions as well as online videos for the reinforcement learning course hosted by Paderborn University
Project mention: PGWAD pool updates and some learning materials | reddit.com/r/CardanoStakePools | 2022-03-07 -
JustEnoughScalaForSpark
A tutorial on the most important features and idioms of Scala that you need to use Spark's Scala APIs.
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You could look into jupyterWith. With that you can list the packages you want to use in a shell.nix file; based on this file an environment is created in which Jupyter is run. I've also had issues with using packages with regular IHaskell in the past, but jupyterWith works pretty well for me.
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Project mention: [OC] Lionel Messi's shots and goals with Barcelona during his record-breaking 2011/2012 season, compared to his attempts in the 2014 and 2018 World Cups with Argentina | reddit.com/r/dataisbeautiful | 2021-12-21
I was pointed to the Huffington Post data by this great repo: https://github.com/rjtavares/football-crunching (which, coincidentally, I found because of this Reddit post: https://www.reddit.com/r/datascience/comments/rh22z9/ive_made_a_search_engine_with_5000_quality_data/ by u/khanarree
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get-started-with-JAX
The purpose of this repo is to make it easy to get started with JAX, Flax, and Haiku. It contains my "Machine Learning with JAX" series of tutorials (YouTube videos and Jupyter Notebooks) as well as the content I found useful while learning about the JAX ecosystem.
Project mention: Machine Learning with JAX - From Hero to HeroPro+ | Tutorial #2 | reddit.com/r/deeplearning | 2021-11-04Code: https://github.com/gordicaleksa/get-started-with-JAX
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Project mention: Why is autosave off by default whenever I launch a Jupyter notebook server? | reddit.com/r/JupyterNotebooks | 2021-10-26
Sorry I cannot help with classic Jupyter Notebook but in JupyterLab you can configure the autosave interval in the Advanced Settings Editor in Document Manager section - no extensions need. Is about time to migrate; if you like the old interface please check out RetroLab https://github.com/jupyterlab/retrolab (and the built-in simple mode)
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I’ve actually solved a similar problem several times in a variety of settings. I’ve had success with boosted trees and feature engineering on the sensor readings over time. I treat each reading as an observation and set the target to be the value I want to forecast (e.g. one hour ahead, the sum over the next day, the value at the same time the next day). There was a recent paper that compared boosted trees to deep learning techniques and found the boosted trees performed really well. Next, I perform feature engineering to aggregate the data up to the current time. These features will include the current value, lagged values over multiple observations for that sensor, more complicated features from moving statistics over different time scales, etc. I actually wrote a blog about creating these features using the open-source package RasgoQL and have similar types of features shared in the open-source repository here. I have also had success creating these sorts of historical features using the tsfresh package. Finally, when evaluating the forecast, use a time based split so earlier data is used to train the model and later data to evaluate the model.
Jupyter Notebook Jupyter related posts
- How to use Jupyter notebooks in a conda environment?
- Python-Fundamentals: NEW Data - star count:138.0
- Python-Fundamentals: NEW Data - star count:138.0
- Python-Fundamentals: NEW Data - star count:138.0
- Python-Fundamentals: NEW Data - star count:138.0
- Python-Fundamentals: NEW Data - star count:138.0
- Python-Fundamentals: NEW Data - star count:138.0
Index
What are some of the best open-source Jupyter projects in Jupyter Notebook? This list will help you:
Project | Stars | |
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1 | homemade-machine-learning | 19,279 |
2 | PRML | 10,534 |
3 | notebook | 9,058 |
4 | py | 4,898 |
5 | nbdev | 3,244 |
6 | fastpages | 3,191 |
7 | beakerx | 2,627 |
8 | ML-Workspace | 2,558 |
9 | alphalens | 2,282 |
10 | Interactive Parallel Computing with IPython | 2,197 |
11 | pytorch-GAT | 1,608 |
12 | IRkernel | 1,484 |
13 | python-training | 1,245 |
14 | reinforcement_learning_course_materials | 728 |
15 | JustEnoughScalaForSpark | 634 |
16 | intro-to-python | 619 |
17 | IElixir | 340 |
18 | jupyterWith | 336 |
19 | football-crunching | 277 |
20 | get-started-with-JAX | 258 |
21 | retrolab | 238 |
22 | learn-you-a-haskell-notebook | 223 |
23 | feature-engineering-tutorials | 188 |
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