Photo taken from Kaggle

Table of Contents

  1. Problem statement
  2. Problem Description
  3. Data Overview
  4. Mapping the problem into supervised learning problem
  5. Business objectives and constraints
  6. Performance metric for supervised learning
  7. EDA
  8. Feature Engineering
  9. Explanation for Bag Of Words (BOW), TF-IDF, Singular Value Decomposition(SVD)
  10. Machine Learning Models
  11. Result Summary
  12. Model Productionization
  13. Future Works
  14. My GitHub and LinkedIn
  15. References

1.Problem statement:

Predict an employee’s access needs, given his/her job role.

2.Problem Description:

When an employee at any company starts work, they first need to obtain the computer access necessary to fulfill their role. This access may allow an employee to read/manipulate resources through various applications or web portals. It is assumed that employees fulfilling…

Photo by Solen Feyissa on Unsplash

Table Of Contents

  1. Problem Statement
  2. Problem Description
  3. Research-Paper
  4. Data Preparation and Overview
  5. Mapping the problem into Deep Learning problem
  6. Business objectives and constraints
  7. Performance metric for Deep Learning
  8. Data Preprocessing & EDA
  9. Encoder Decoder based Sequence to Sequence model(This section contains explanation and implementation of the Train and Inference models)
  10. Attention Model (This section implements Attention model and shows how we can improve the existing Seq2Seq model)
  11. Evaluate the Model’s predicted answers using BLEU Score
  12. Conclusion
  13. Future Works
  14. My GitHub and LinkedIn
  15. References

1. Problem Statement:

Create an end-to-end method for automatically generating short email responses, called Smart Reply.

2. Problem Description:

Email is one of the most popular…

Pratik Sen

Machine Learning || NLP || Deep Learning

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