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do sentiment analysis, text classification, topic modelling, clustering in nlp

jidiv
jidiv
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Hello,


I am a Post Graduate in Artificial Intelligence with a 10 years of background in Investing(CFA - L2 Cleared).


With over 2 years of experience in extensively solving various business problems by applying Natural Language Processing (NLP), I am better equipped to solve your NLP related problems.


I enjoy solving NLP related challenges and enjoy helping people with their task of understanding language and making sense out of it for their business needs.



Few of the problems I have solved are based on: -

  1. Intent Classification
  2. Text Generation, Summarization
  3. Topic Modeling
  4. Semantic Search Using Cosine Similarity, Keyword based search
  5. Clustering
  6. Text Classification


I have made extensive use of the following models for solving NLP related challenges:-


  1. BERT
  2. T5 - Transformer
  3. GPT 1,2,3
  4. RoBERTa
  5. DistilBERT
  6. BART
  7. LSTM
  8. RNNs
  9. Encoder - Decoder
  10. KNN
  11. SVM
  12. LR
  13. Decision Tree
  14. XGBoost
  15. LGBM


Frameworks I have used are:-


  1. Tensorflow
  2. Keras
  3. Pytorch


Tools & Platforms:-


  1. Google Cloud
  2. Microsoft Azure
  3. Jupyter Notebook
  4. Colab
  5. Paperspac


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