semvec/pypi-packages huggingface dataset:
AgainML 0.1.1
Machine Learning Algorithms implemented from scratch in Python
Requires Python: >=3.6

# Machine Learning And Deep Learning Algorithms from Scratch

In this repository, major machine learning and deep learning algorithms are implemented from scratch. From scratch meaning without using external machine learning libraries. All of the below mentioned algorithms are implemented in Python, Linear Regression is also implemented in C++. The API structure is similar to the Scikit-Learn library and Tensorflow Keras API.

<hr>

## Algorithms:

#### Supervised Learning:
  1. <a href="https://github.com/NotShrirang/Machine-Learning-from-Scratch/tree/main/LinearRegression">Linear Regression</a>
  2. <a href="https://github.com/NotShrirang/Machine-Learning-from-Scratch/tree/main/K-nearest%20Neighbours">K-nearest Neighbours</a>
  3. <a href="https://github.com/NotShrirang/Machine-Learning-from-Scratch/tree/main/Support%20Vector%20Machine">Support Vector Machine</a>
  4. <a href="https://github.com/NotShrirang/Machine-Learning-from-Scratch/tree/main/Neural%20Networks">Artificial Neural Networks</a>

#### Unsupervised Learning:
  1. <a href="https://github.com/NotShrirang/Machine-Learning-from-Scratch/tree/main/K-Means%20Clustering">K-Means Clustering</a>
  2. <a href="https://github.com/NotShrirang/Machine-Learning-from-Scratch/tree/main/Mean%20Shift%20Clustering">Mean Shift Clustering</a>
  
<hr>

## Deep Learning:
<a href="https://github.com/NotShrirang/Machine-Learning-from-Scratch/tree/main/Neural%20Networks">Neural Networks</a> added with ReLU, Softmax Activations and Categorical Cross Entropy losses, and Optimizers such as SGD, Adam.

To use this implementation:

```
pip install open-nn-python
```