You will get Multi-Algorithm Text Summarization Tool Using Streamlit


Project details
This project provides a fully functional Text Summarization Application built using Python and Streamlit. Whether you're looking to analyze long documents, academic papers, or articles, this app can compress them into key points using advanced NLP techniques.
Features:
• Choose Your Algorithm: Supports LSA, Luhn, LexRank, and TextRank
• Customizable Summary Length: Decide how many sentences you want in your summary
• Streamlit Interface: User-friendly UI for quick summaries
• Ready to Deploy: Code is clean and ready for local or cloud deployment
Features:
• Choose Your Algorithm: Supports LSA, Luhn, LexRank, and TextRank
• Customizable Summary Length: Decide how many sentences you want in your summary
• Streamlit Interface: User-friendly UI for quick summaries
• Ready to Deploy: Code is clean and ready for local or cloud deployment
Machine Learning Tools
NLTK, PythonWhat's included
| Service Tiers |
Starter
$20
|
Standard
$40
|
Advanced
$60
|
|---|---|---|---|
| Delivery Time | 2 days | 3 days | 5 days |
Number of Revisions | 0 | 0 | 0 |
Model Validation/Testing | - | - | - |
Model Documentation | - | - | - |
Data Source Connectivity | - | - | - |
Source Code | - | - | - |
About Mona
Machine Learning Engineer
Cairo, Egypt - 6:24 pm local time
Programming & Tools: Python, TensorFlow, Keras, Scikit-learn, NumPy, Pandas, Matplotlib, Seaborn
Machine Learning: Supervised & Unsupervised Learning, Regression, Classification, Clustering, Model Evaluation
Deep Learning: Neural Networks, CNNs, RNNs, Transfer Learning
Data Processing: Data Cleaning, Feature Engineering, Data Visualization, Handling Imbalanced Data
Other Tools: Jupyter Notebook, Google Colab, Git/GitHub
Soft Skills: Analytical Thinking, Problem Solving, Attention to Detail, Clear Communication
Steps for completing your project
After purchasing the project, send requirements so Mona can start the project.
Delivery time starts when Mona receives requirements from you.
Mona works on your project following the steps below.
Revisions may occur after the delivery date.
Review Client Requirements
I will review the input text, chosen algorithm(s), and summary length provided by the client.
Develop and Customize the Summarization Code
I will build or customize the text summarization script using the selected algorithm(s) and parameters.
