condo-adapter
Confounded Domain Adapter (by calvinmccarter)
ML-foundations
Machine Learning Foundations: Linear Algebra, Calculus, Statistics & Computer Science (by jonkrohn)
| condo-adapter | ML-foundations | |
|---|---|---|
| 2 | 1 | |
| 3 | 2,984 | |
| - | - | |
| 3.7 | 5.4 | |
| about 1 year ago | 21 days ago | |
| Jupyter Notebook | Jupyter Notebook | |
| Creative Commons Attribution Share Alike 4.0 | 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.
condo-adapter
Posts with mentions or reviews of condo-adapter.
We have used some of these posts to build our list of alternatives
and similar projects.
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Great thread on the importance of EDA and confounder adjustment prior to differential expression analysis (RNA-seq)
Fwiw, last week I released a new method for batch correction that conditions on confounders which are correlated with the batch variable. Preprint here: https://arxiv.org/abs/2203.12720 and Python code here: https://github.com/calvinmccarter/condo-adapter.
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New method for batch correction confounded by outcome distribution
Software (Python) is here: https://github.com/calvinmccarter/condo-adapter
ML-foundations
Posts with mentions or reviews of ML-foundations.
We have used some of these posts to build our list of alternatives
and similar projects.
-
Worried about Calculus
As others have said, you won't need calculus immediately, but it's important that you make a good attempt at learning up to Calc3. I also didn't have a math heavy undergrad so it took a lot of self-study for me, but it's possible. Simulation has a great math boot camp at the beginning to review everything but you'll want to be prepped with Calc before that because that class is all calculus based probability. Some other good resources are the 3Blue1Brown videos on YouTube. They have a great series for both calc & linear algebra to talk through all the intuition with visuals. I also really like John Krohns series because you code through the math which is very applicable for us in this program. I only did his linear Algebra, but he has a whole series with Calc and probability, too. https://github.com/jonkrohn/ML-foundations