Clustering algorithm using Python packages

Course Q&A Machine Learning Specialization Unsupervised Learning, Recommenders, Reinforcement
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In the W1 Lab1 clustering algorithm was introduced in Python using numpy package, e. g. we’ve build clustering algorithm from scratch.
Can someone provide Python packages to build clustering algorithm, like from scikit-learn or something like that?

week-1

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Scikit-learn, which you mentioned, provides a variety of clustering algorithms, including K-Means, Agglomerative Clustering, and DBSCAN, etc. It can also integrate with popular frameworks like TensorFlow and PyTorch by converting tensors to NumPy arrays. You can also manually implement clustering algorithms in TensorFlow, PyTorch or NumPy.
SciPy package provides K-Means algorithm and also includes hierarchical clustering and distance metrics.
There are also high-performant standalone implementations of DBSCAN and HDBSCAN.

1 Like
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Hi @D1ZER99,

I hope you are doing well. To create a clustering algorithm using Python, you can utilize several libraries, such as Scikit-learn, SciPy, HDBSCAN, PyClustering, and TensorFlow Keras, among others.

If you prefer to build your own custom clustering algorithm, you can make use of the following tools:

  1. NumPy: For numerical computations and handling multi-dimensional arrays.
  2. SciPy: For mathematical operations, including functions specific to clustering, such as calculating pairwise distances and performing hierarchical clustering.
  3. Pandas: Useful for handling and preprocessing datasets, especially if your data is tabular. It assists in filtering, cleaning, and transforming data before applying clustering.
  4. Matplotlib/Seaborn: Helpful for visualizing data to understand and debug clustering algorithms.
  5. SymPy: For algorithms that require symbolic computation or solving mathematical expressions.
  6. Numba: To accelerate computation-heavy parts of your algorithm by compiling Python code to machine code.

Please feel free to ask if you have any doubts.