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Hi there, I love your tutorials! They helped me a lot while I'm doing my internship. I'm wondering if you have any interest in machine learning, specifically supervised deep learning using tensorflow?…
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To keep the scope of this article focused, the tips should be about deep learning in biology. Several tips only pertain to one or the other. I recommend we add more biology examples to the tips that…
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- We analyzed various financial and demographic variables to create a machine learning model using the KNN method with the goal of predicting customer inactivity.
- A visual analysis (descriptive sta…
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Utilized Python's BeautifulSoup library for web scraping fbref.com to gather match statistics and EPL teamperformance data.
Cleaned and preprocessed the collected data to ensure consistency and accur…
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## R
- [swcarpentry/r-novice-inflammation](https://github.com/swcarpentry/r-novice-inflammation)
- **Title:** Introduction to R for non-programmers using inflammation data.
- **tags:** [R]
…
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num | name | result | fork | color | tag1 | tag2
-- | -- | -- | -- | -- | -- | --
0 | Bitcoin-and-Cryptocurrency-Technologies | keep | TRUE | | |
1 | CognosTM1-DevKit | keep | TRUE | yellow | …
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Need to add in plots for the accuracy and loss statistics to show improvement of the model through active learning.
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## 🚀 Feature
A deep learning-based time series forecasting library with Pytorch.
## Motivation
Time series forecasting has broad significance in public health, finance, and engineering. Tradit…
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I am trying to implement a simple example with scaled conjugate gradient. This is my code
`
dataset = [Instance( [0,0], [0] ), Instance( [1,0], [1] ), Instance( [0,1], [1] ), Instance…
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The group added basic statistics of each bands as features and also used median for the indices. More reasoning for these decisions might add more context to the machine learning process.