MLOps
End to End toy example of MLOps (by ashishtele)
NLP-CNN-Subreddit-Sorter-Heroku-App
End-to-end development of an application using a convolutional neural network that suggests to users/moderators which technical subreddit a post actually belongs to. Novel method to determine # of CNN filters. Custom Word2vec embeddings. The subreddits chosen are all technical and similar, and benefit users/moderators interested in data science and related fields. (Exploratory data analysis, feature engineering, custom word2vec embeddings, convolutional neural network, deployment via flask to Heroku ) (by djthorne333)
| MLOps | NLP-CNN-Subreddit-Sorter-Heroku-App | |
|---|---|---|
| 1 | 4 | |
| 7 | 1 | |
| - | - | |
| 1.6 | 0.0 | |
| about 1 year ago | about 2 years ago | |
| Jupyter Notebook | Jupyter Notebook | |
| MIT License | - |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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.
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.
MLOps
Posts with mentions or reviews of MLOps.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-01-17.
NLP-CNN-Subreddit-Sorter-Heroku-App
Posts with mentions or reviews of NLP-CNN-Subreddit-Sorter-Heroku-App.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-03-24.
- The outputs of my jupyter notebooks inside of Github repos only show half of what they used to. Why did this happen and how to fix? I am certain that the outputs used to show everything when viewed in Github, and I have not reuploaded the notebooks to the repo's since then.
- The outputs of my jupyter notebooks inside of Github repos only show half of what they used to. Why did this happen and how to fix? I am certain that the outputs used to show everything when viewed in Github.
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I created an app (CNNet, URL in description) that tells you what subreddit to post to based on your title, and I used r/Python, r/learnmachinelearning, r/compsci and r/datascience. This app could be expanded to include other technical subreddits and serve as a way to decide where to crosspost.
This app could be expanded to include other similar technical subreddits and serve as a way to decide where to crosspost, or for moderators to auto flag posts that are off topic. Here is the repo: https://github.com/djthorne333/NLP-CNN-Subreddit-Sorter-Application, and link to the app: https://datascience-reddit-post-sorter.herokuapp.com/. I think I thought of a way to extract from the dataset the optimal amount of filters to use for each filter size for the CNN. I have some typos to fix right now it seems, but it's generally done. Please let me know what you think, and give me any advice, as I am trying to break into data science.
What are some alternatives?
When comparing MLOps and NLP-CNN-Subreddit-Sorter-Heroku-App you can also consider the following projects:
VevestaX - 2 Lines of code to track ML experiments + EDA + check into Github
CSGO-Pro-Gear-Performance-and-EDA - Modeling Professional (CS:GO) Gamer's Accuracy Performance Based on Gear and Settings, and Exploratory Data Analysis.
bodywork-pipeline-with-aporia-monitoring - Integrating Aporia ML model monitoring into a Bodywork serving pipeline.
fellowship-prediction - Analyzes your GitHub Profile and presents you with a report on how likely you are to become the next MLH Fellow!
mlflow-deployments - Source code for the post Effortless deployments with MLFlow, showcasing how logging models using MLFLow can provide you want to easily deploy them in production later.