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1. End-to-End-Credit-Card-Fraud-Detection End-to-End-Credit-Card-Fraud-Detection Public

   This repository contains the procedure we followed to deploy our web app of Credit Card Fraud detection on Heroku. Since the data for credit card fraud is not available in real form(due to confiden…

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2. Emotion-detector-for-Twitter-messages Emotion-detector-for-Twitter-messages Public

   • Trained and deployed emotion detector with Word Embeddings, LSTM, BERT using TensorFlow and Transformers. • Fine tunned the Bert-base-cased Encoder Transformer with Tensorflow classification head…

   Jupyter Notebook 2

3. Predicting_customer_churn Predicting_customer_churn Public

   • Did in depth exploratory data analysis on the churn dataset and got valuable insight for the machine learning model. • Created a machine learning model using a bunch of algorithms (LR, KNN, SVC, …

   Jupyter Notebook 2

4. Amazon-Food-Reviews-Sentiment-Analysis Amazon-Food-Reviews-Sentiment-Analysis Public

   • Conducting Sentiment Analysis of customer feedback on food items through the use of Machine Learning techniques. • Built a sentiment Classifier using LSTM along with various embedding techniques …

   Jupyter Notebook

5. Data_Extraction_and_Text_Analysis_for_Blackcoffer_company. Data_Extraction_and_Text_Analysis_for_Blackcoffer_company. Public

   The objective of this assignment is to extract textual data articles from the given URL and perform text analysis to compute variables that are explained

   Jupyter Notebook 27 40

6. INSAID_fruad_detection_model INSAID_fruad_detection_model Public

   This case requires trainees to develop a model for predicting fraudulent transactions for a financial company and use insights from the model to develop an actionable plan.

   Jupyter Notebook 1 1