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George Mihaila
2020-10-29 14:53:03 -05:00
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@@ -64,7 +64,7 @@ All function implemented in the **ml_things** module.
Array manipulation related function that can be useful when working with machine learning.
#### pad_array [[source]](https://github.com/gmihaila/ml_things/blob/efb2574a9935c6a6ef62135efba2d965b2044175/src/ml_things/array_functions.py#L21)
#### pad_array [[source]](https://github.com/gmihaila/ml_things/blob/master/src/ml_things/array_functions.py#L21)
Pad variable length array to a fixed numpy array. It can handle single arrays [1,2,3] or nested arrays [[1,2],[3]].
@@ -87,7 +87,7 @@ array([[ 1., 2., 99., 99., 99.],
[ 4., 5., 6., 99., 99.]])
```
#### batch_array [[source]](https://github.com/gmihaila/ml_things/blob/efb2574a9935c6a6ef62135efba2d965b2044175/src/ml_things/array_functions.py#L120)
#### batch_array [[source]](https://github.com/gmihaila/ml_things/blob/master/src/ml_things/array_functions.py#L120)
Split a list into batches/chunks. Last batch size is remaining of list values.
**Note:** *This is also called chunking. I call it batches since I use it more in ML.*
@@ -105,7 +105,7 @@ The last batch will be the reamining values:
Plot related function that can be useful when working with machine learning.
#### plot_array [[source]](https://github.com/gmihaila/ml_things/blob/efb2574a9935c6a6ef62135efba2d965b2044175/src/ml_things/plot_functions.py#L23)
#### plot_array [[source]](https://github.com/gmihaila/ml_things/blob/master/src/ml_things/plot_functions.py#L29)
Create plot from a single array of values.
@@ -116,10 +116,10 @@ All arguments are optimized for quick plots. Change the `magnify` arguments to v
>>> plot_array([1,3,5,3,7,5,8,10], path='plot_array.png', magnify=0.1, use_title='A Random Plot', start_step=0.3, step_size=0.1, points_values=True, use_ylabel='Thid', use_xlabel='This')
```
![plot_array](https://github.com/gmihaila/ml_things/raw/master/tests/test_samples/plot_array.png)
![plot_array](https://github.com/gmihaila/ml_things/blob/master/tests/test_samples/plot_array.png)
#### plot_dict [[source]](https://github.com/gmihaila/ml_things/blob/efb2574a9935c6a6ef62135efba2d965b2044175/src/ml_things/plot_functions.py#L183)
#### plot_dict [[source]](https://github.com/gmihaila/ml_things/blob/master/src/ml_things/plot_functions.py#L243)
Create plot from a single array of values.
@@ -132,10 +132,10 @@ All arguments are optimized for quick plots. Change the `magnify` arguments to v
start_step=0.3, step_size=0.1,path='plot_dict.png', points_values=[True, False], use_title='Title')
```
![plot_dict](https://github.com/gmihaila/ml_things/raw/efb2574a9935c6a6ef62135efba2d965b2044175/tests/test_samples/plot_dict.png)
![plot_dict](https://github.com/gmihaila/ml_things/blob/master/tests/test_samples/plot_dict.png)
#### plot_confusion_matrix [[source]](https://github.com/gmihaila/ml_things/blob/efb2574a9935c6a6ef62135efba2d965b2044175/src/ml_things/plot_functions.py#L360)
#### plot_confusion_matrix [[source]](https://github.com/gmihaila/ml_things/blob/master/src/ml_things/plot_functions.py#L471)
This function prints and plots the confusion matrix. Normalization can be applied by setting `normalize=True`.
@@ -149,14 +149,14 @@ array([[1, 1],
[1, 3]])
```
![plot_confusion_matrix](https://github.com/gmihaila/ml_things/raw/efb2574a9935c6a6ef62135efba2d965b2044175/tests/test_samples/plot_confusion_matrix.png)
![plot_confusion_matrix](https://github.com/gmihaila/ml_things/blob/master/tests/test_samples/plot_confusion_matrix.png)
### Text Functions
Text related function that can be useful when working with machine learning.
#### clean_text [[source]](https://github.com/gmihaila/ml_things/blob/efb2574a9935c6a6ef62135efba2d965b2044175/src/ml_things/text_functions.py#L22)
#### clean_text [[source]](https://github.com/gmihaila/ml_things/blob/master/src/ml_things/text_functions.py#L22)
Clean text using various techniques:
@@ -170,7 +170,7 @@ Clean text using various techniques:
Web related function that can be useful when working with machine learning.
#### download_from [[source]](https://github.com/gmihaila/ml_things/blob/efb2574a9935c6a6ef62135efba2d965b2044175/src/ml_things/web_related.py#L21)
#### download_from [[source]](https://github.com/gmihaila/ml_things/blob/master/src/ml_things/web_related.py#L21)
Download file from url. It will return the path of the downloaded file: