similarity_measures
Made-With-ML
| similarity_measures | Made-With-ML | |
|---|---|---|
| 2 | 51 | |
| 237 | 35,702 | |
| - | - | |
| 5.4 | 6.8 | |
| 6 months ago | 5 months ago | |
| Jupyter Notebook | Jupyter Notebook | |
| MIT License | MIT License |
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.
similarity_measures
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What exactly is Partial Curve Mapping?
The Python Implementation can be found here: https://github.com/cjekel/similarity_measures/blob/master/similaritymeasures/similaritymeasures.py
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Anyone here use the Similaritymeasures library? Why is a 2D array required?
According to the documentation the function takes two arguments (exp_data and num_data ) for the data set, which makes sense. What doesn't make sense is:
Made-With-ML
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[D] How do you keep up to date on Machine Learning?
Made With ML
- Open-Source Production Machine Learning Course
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Advice for switching careers within analytics
- Develop a (simple!) ML project and apply MLOps best practices to it. Ask Chat GPT all of your MLOps questions. I've joined this MLOps community and it has been very helpful to know what path to follow in order to be better at MLOps, thanks to them I arrived at madewithml, but I haven't done it yet. But it covers all the MLOps side.
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Recommendation for MLOps resources
Hey, I’m also working in ML. Here’s a great resource: https://madewithml.com. Also, check out Noah Gift’s book Practical MLOPs.
- Ask HN: Resource to learn how to train and use ML Models
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Need help to find resources to learn ml ops
Try replicating this setup: https://madewithml.com/
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MLops Resources
madewithml
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Ask HN: How do I get started with MLOps?
There's a really nice website by Goku Mohandas called Made With ML. IMO it is the best practical guide to MLOps out there: https://madewithml.com
Incase you want to dive a little deeper, https://fullstackdeeplearning.com/course/2022/ is also something I have been recommended by folks.
- Resources for Current DE Interested in Learning Data Science
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Do organizations still need machine learning engineers?
madewithml is pretty sweet, especially the MLOps side of things. It'll give you good skills in how development in Python and deploying ML works.
What are some alternatives?
zero-to-mastery-ml - All course materials for the Zero to Mastery Machine Learning and Data Science course.
mlops-zoomcamp - Free MLOps course from DataTalks.Club
FLAML - A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.
mlops-course - Learn how to design, develop, deploy and iterate on production-grade ML applications.
practical-mlops-book - [Book-2021] Practical MLOps O'Reilly Book
Copulas - A library to model multivariate data using copulas.
ETCI-2021-Competition-on-Flood-Detection - Experiments on Flood Segmentation on Sentinel-1 SAR Imagery with Cyclical Pseudo Labeling and Noisy Student Training
awesome-mlops - A curated list of references for MLOps
mlattacks - Machine Learning Attack Series
SBERT-for-Question-Answering-on-COVID-19-Dataset - Sentence Bert for Question-Answering on COVID-19 Open Research Dataset (CORD-19)
fake-s3 - A lightweight server clone of Amazon S3 that simulates most of the commands supported by S3 with minimal dependencies
stanford-cs229 - 🤖 Exercise answers to the problem sets from the 2017 machine learning course cs229 by Andrew Ng at Stanford