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Yeshiwas1985/Amharic-News-Classification-Using-LSTM-Bidirectional-LSTM-and-GRU

Domain:

natural language processing

Record type:

dataset
Creator:
Yes
Host:
# Amharic News Classification Using LSTM, Bidirectional-LSTM, and GRU ### I have collected 24,000 news from different news sources in Ethiopian media. ### Then I categorized the dataset into 6 classes. namely: ### 1. የሃገር ዉስጥ ዜና (Local News) #### 2. ፖለቲካ (Politics News) #### 3. ቢዝነስ (Business News) #### 4. አለምአቀፋዊ ዜና (International News) #### 5. መዝናኛ (Entertainment News) #### 6. ስፖርት (Sport News) ## Data Preprocessing: I have applied different data-preprocessing methods to make the dataset clean. such as ### 1. Removing any missing value from the whole dataset ### 2. Normalization To normalize character level mismatch such as "ጸሀይ" and "ፀሐይ" and others. #### 3. Removing Special Characters Removing any special character from the article column. ### 4. Removing Stopwords Removing the stopwords from the article column using the set Amharic stopwords # Models Used: ### 1. LSTM (Long Short Term Memory) ### 2. Bidirectional LSTM ### 3. Gated Recurrent Unit ### 4. Word2vec ## N.B: if you need a dataset, contact me using LinkedIn linkedin.com

Visit

github.com

Tasks

news classificationtopic classificationtext classification

Languages

Amharic

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