文件列表:

artifacts/
config/
src/bbc_news/
static/
templates/
app.py
dvc.yaml
main.py
params.yaml
requirements.txt
setup.py

# BBC News Classification LSTM In today’s world, data is power. With News companies having terabytes of data stored in servers, everyone is in the quest to discover insights that add value to the organization. With various examples to quote in which analytics is being used to drive actions, one that stands out is news article classification. Nowadays on the Internet there are a lot of sources that generate immense amounts of daily news. In addition, the demand for information by users has been growing continuously, so it is crucial that the news is classified to allow users to access the information of interest quickly and effectively. This way, the machine learning model for automated news classification could be used to identify topics of untracked news and/or make individual suggestions based on the user’s prior interests. **Approach:** Techniques like clustering and associating rule-based algorithms can be applied to group together similar text. The ML algorithms learn the mapping function between the text and the tags based on already categorized data. Algorithms such as SVM, Neural Networks, Random Forest are commonly used for text classification. **Results:** For a given news article, the system should be able to classify them according to various categories like Finance, Sports etc. You have to build a solution that should recognize and classify the news articles based on their labels. Text documents are one of the richest sources of data for businesses.We’ll use a public dataset from the BBC comprised of 2225 articles, each labeled under one of 5 categories: business, entertainment, politics, sport or tech. The dataset is broken into 1490 records for training and 735 for testing. The goal will be to build a system that can accurately classify previously unseen news articles into the right category. ### [Click Here To See More About The Dataset](https://www.kaggle.com/c/learn-ai-bbc/data) ## ML Flow Experiments # How to run? ### STEPS: Clone the repository ```bash https://github.com/SunilKumar-ugra/BBC_News_Classification_LSTM.git ``` ### STEP 01- Create a conda environment after opening the repository ```bash conda create -n bbc-news python=3.8 -y ``` ```bash conda activate bbc-news ``` ### STEP 02- install the requirements ```bash pip install -r requirements.txt ``` ```bash # Finally run the following command python app.py ``` Now, ```bash http://127.0.0.1:80 #Open this url in the browser ``` ## Project Demo

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