You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
OCR, extract and classify documents. In addition, annotate documents and build your own NLP and Computer Vision models using Python by downloading the data. Find examples in our Colab Notebooks, e. g. how to fine-tune Flair.
Extract text content from an HTML page, process it, and extract unique words from the processed text. This notebook utilizes various text processing techniques including cleaning, normalization, tokenization, lemmatization or stemming, and stop words removal.
Basic text preprocessing operations shown in jupyter notebook. You can play with them and look what are they doing. For stemming and lemmatization there are different options, I showed only what I prefer to use. Repository contains the data to play with taken from kaggle (can also be found here on github), but for convenience I attach it here.
The notebook classifies reddit posts to its respective subreddit using different machine learning models and Compares the performance of these models. And finds the best model.
Ipython Notebooks for solving problems like classification, segmentation, generation using latest Deep learning algorithms on different publicly available text and image data-sets.