i.mlearning

v2.3.43

10 days ago

mLearning about all.this.

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i.mlearning is a comprehensive toolkit designed to standardize and streamline machine learning for the web.

To begin using i.mlearning, follow these steps:

Install the Package:
Run the following command to install i.mlearning via npm:
```
npm install i.mlearning
```
Import and Use:
After installation, you can import and use i.mlearning in your project:
```
import mLearning from 'i.mlearning';
```

Training set (m_train): This is the dataset you use to teach the machine learning algorithm. It contains both the features (the input data) and the labels (the correct output or the target). The algorithm uses this data to learn patterns, relationships, and the overall structure of the data. The model adjusts its internal parameters during training based on the comparison between the predicted output and the actual labels (this process is called learning).
Test set (m_test): This is a separate dataset that you use to evaluate the performance of the model after it has been trained. The test set also contains both features and labels, but the key difference is that the algorithm has not seen this data during training. Once the model is trained on the training set, you run it on the test set and compare its predictions to the actual labels to assess how well it generalizes to new, unseen data.

You train the algorithm on the training set.
Then, you use the test set to evaluate how well the model learned by comparing the predicted results with the actual labels.
Both the training and test sets are labeled datasets, meaning they contain the correct answers or target values you are trying to predict.

These classes encapsulate the functionalities to domain-specific data.

License: MIT License (see LICENSE for details).
Privacy Policy: Respects user privacy; no collection/storage of personal data.
Terms of Usage: Use responsibly. No guarantees/warranties provided. Terms | Privacy neurons.me