NLP text summarizer, is a Python package that summarizes texts and extracts the most important sentences from a given text. Text summarizer is commonly used in news feeding websites to summarize long articles. Summarizer shortens long texts such that the summarized text preserves all the essential points of the actual text. It uses spaCy, nltk, and NumPy to do the job. This solution is also used to summarize texts (in Extractive and abstractive techniques), extract key sentences and find their TF-IDF values. How can you build a similar model?
The answer is in this course using the kandi 1-click solution kit. You will have a working model at the end of the session!
After completing this course you will:
- Have a good working knowledge of the Fundamentals of Natural Language Processing.
- Learn various concepts involved in building the Text summarizer such as sentence embedding, HuggingFace transformers, and BERT model.
- Have a fully functional text summarizer that you can customize, showcase, and share, using the existing source code.
- Be able to fine tune the parameters to enhance its result.
Complete this course in 3 easy steps to earn your certificate!
STEP 1 : Watch the below self-guided tutorial.
STEP 2 : Practice as you watch the video by installing and working with the kandi 1-click solution kit.
STEP 3 : Complete the assessment to receive your certificate.
STEP 1 : TUTORIAL
Watch this self-guided tutorial on installing dependencies, loading pre-trained model, and testing a NLP based solution to build your Text Summarizer in Python.
STEP 2 : PRACTICAL EXERCISE
Click the below button to access the text summarizer kandi kit. This kit has all the required dependencies and resources you need to build your application.
Click on the 1-Click Installer button on the kandi kit page to install the text summarizer kit. On installing and running this kit, you will have a working model that you can customize and use in your project.
After completing this step, proceed to STEP 3.
STEP 3 : ASSESSMENT
Your assessment will be reviewed and you will receive a verified certificate via email within a week.
Reach out to us by replying below for any help you may need with this course.
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