Suhail-Shaikh-96

Banking_System-in-Java

Banking System using Java

Building-Multiple-Regression-model-to-predict-Sales

Multiple Regression

Classifying-text-articles-into-one-of-the-four-categories-based-on-Bag-of-words-from-set-of-articles

Multiclass ‘Support vector Machine” (1 vs all) model with the help of Binary SVM model to classify text articles into one of the four categories

Classifying-Tweet-as-Fact-or-Misinformation

Correlation-ANOVA-testing-to-Analyze-relationship-of-variables-in--Employee-performance-dataset

Correlation and ANOVA

Creating-Mapper-and-reducer-for-count-of-words-in-the-book-Pride_and_Prejudice-

Created Mapper and Reducer function in Python using Multi threading concept to represent Hadoop Infrastructure for counting of words in the book "Pride_and_Prejudice"

Improving-Customer-Engagement-at-VMWARE-through-Analytics-Harvard-Business-Case-Study-

VMWare-Analytics-Harward-Business-Case-Study-

Language-translation-using-Deep-Neural-networks

Created LSTM model (a special kind of recurrent neural network) for speech translation using TensorFlow where output language is English and input language is Marathi. Used Glove 100 dimensional embeddings for training the LSTM model. Evaluated model by converting input from English to Marathi.

Movie-Recommendation-using-Embeddings

Created movie embeddings vectors based on a model that generates similar vectors for movies watched by similar people. Optimized the cost function using gradient descent in Pytorch and generated 10 recommendations for the user-entered movies.

Predicting-Net-Promoter-Score-to-Improve-patient-Experience-at-Manipal-Hospitals-Harvard-CaseStudy-

Predicting-NPS-Score-Harward-Business-Case-Study-

Suhail-Shaikh-96/Improving-Customer-Engagement-at-VMWARE-through-Analytics-Harvard-Business-Case-Study-

VMWare-Analytics-Harward-Business-Case-Study-

Suhail-Shaikh-96/Predicting-Net-Promoter-Score-to-Improve-patient-Experience-at-Manipal-Hospitals-Harvard-CaseStudy-

Predicting-NPS-Score-Harward-Business-Case-Study-

Suhail-Shaikh-96/Language-translation-using-Deep-Neural-networks

Created LSTM model (a special kind of recurrent neural network) for speech translation using TensorFlow where output language is English and input language is Marathi. Used Glove 100 dimensional embeddings for training the LSTM model. Evaluated model by converting input from English to Marathi.

Suhail-Shaikh-96/Movie-Recommendation-using-Embeddings

Created movie embeddings vectors based on a model that generates similar vectors for movies watched by similar people. Optimized the cost function using gradient descent in Pytorch and generated 10 recommendations for the user-entered movies.

Suhail-Shaikh-96/Banking_System-in-Java

Banking System using Java

Suhail-Shaikh-96/Building-Multiple-Regression-model-to-predict-Sales

Multiple Regression

Suhail-Shaikh-96/Classifying-text-articles-into-one-of-the-four-categories-based-on-Bag-of-words-from-set-of-articles

Multiclass ‘Support vector Machine” (1 vs all) model with the help of Binary SVM model to classify text articles into one of the four categories

Suhail-Shaikh-96/Classifying-Tweet-as-Fact-or-Misinformation

Suhail-Shaikh-96/Correlation-ANOVA-testing-to-Analyze-relationship-of-variables-in--Employee-performance-dataset

Correlation and ANOVA

Suhail-Shaikh-96/Creating-Mapper-and-reducer-for-count-of-words-in-the-book-Pride_and_Prejudice-

Created Mapper and Reducer function in Python using Multi threading concept to represent Hadoop Infrastructure for counting of words in the book "Pride_and_Prejudice"

Suhail-Shaikh-96/Decision-Tree-and-Cross-Validation-implementation-on-Wine-Dataset-to-predict-quality-of-wine

Decision Tree and Cross Validation

Suhail-Shaikh-96/Descriptive-Statistics-DecisionTree-on-datasets-named-attitude-Exercise-Diabetes-Birtwt-

Descriptive Statistics and Decision Tree in R

Suhail-Shaikh-96/Descriptive-statistics-Random-Forest-Logistic-Regression-ROC-and-AUC-Curve-on-German-Credit-Data

Random Forest and Logistic Regression

Suhail-Shaikh-96/KMeans-Clustering-to-cluster-customers-based-on-different-variables-that-determin-their-credit-score

K Means Clustering in R

Suhail-Shaikh-96/Transfer-Learning-using-CIFAR-10-dataset