References
This is our Python Guide for ML development. See Table 1. Below
::: pandas
1. Data
Here is the mycelium data classes.
| Method | Description |
|---|---|
mycelium.Inchworm() |
A class of functions that scrapes data and converts data between different formats (HTML and JSON) and retrieve HTML content from a given URL. |
mycelium.Dataset() |
A class of methods for loading, organizing, and summarizing different types of data. |
|
2. Models
All our models are end-to-end, meaning all components are "capable" of training jointly online. The are also explainable. They are also highly accurate (think semantical in a heirarchical tree embedding logic through a back propoagation pruning way).
| Method | Description |
|---|---|
mycelium.Psilocybin() |
An class of ML for image generation encoding and decoding using - u-net (CNNs) and automatic hierarchical feature recognition. Furthermore, they are robust to variations in images, such as changes in size, rotation, or illumination, enhancing their performance and versatility in diverse real-world scenarios. |
mycelium.Hyphae() |
A class of large-scale, Transformer-based model pre-trained on multilingual data, generating contextual word representations, capable of transfer learning for various NLP tasks including machine translation, sentiment analysis, and more. |
|
3. Analytics
| Method | Description |
|---|---|
mycelium.plot() |
Overall, this class provides a wide range of tools for visualizing and understanding machine learning data. |
|