Python’s Sklearn library provides a great sample dataset generator which will help you to create your own custom dataset. It’s fast and very easy to use. Following are the types of samples it provides.
For all the above methods you need to import
- Learning Model Building in Scikit-learn : A Python Machine Learning Library
- Classifying data using Support Vector Machines(SVMs) in Python
- Introduction To Machine Learning using Python
- Tokenize text using NLTK in python
- Removing stop words with NLTK in Python
- How to get synonyms/antonyms from NLTK WordNet in Python?
- Convert Text to Speech in Python
- Phyllotaxis pattern in Python | A unit of Algorithmic Botany
- Turing Test in Artificial Intelligence
- Data Preprocessing for Machine learning in Python
- Decision tree implementation using Python
- Plotting graph using Seaborn | Python
- Analysis of test data using K-Means Clustering in Python
- R vs Python in Datascience
- Python | Named Entity Recognition (NER) using spaCy
If you like GeeksforGeeks and would like to contribute, you can also write an article using contribute.geeksforgeeks.org or mail your article to email@example.com. See your article appearing on the GeeksforGeeks main page and help other Geeks.
Please Improve this article if you find anything incorrect by clicking on the "Improve Article" button below.