Zamir S.

Zamir S.

Data Scientist: Machine Learning expert

Greater Noida , India

Experience: 14 Years

Zamir

Greater Noida , India

Data Scientist: Machine Learning expert

36000 USD / Year

  • Immediate: Available

14 Years

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About Me

KEK SKILLS: Data Science, Machine Learning, Deep Learning, Natural Language Processing, Spark ML, H2O, Keras, R, Python, Spacy, Rasa
Machine Learning: Supervised, Unsupervised, Decision Tree (CART, ID3, C5.0, CHAID), Random Forest, SV...

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Portfolio Projects

Cold start accessories recommendation Engine

Company

Cold start accessories recommendation Engine

Description

Individual Contributor

Developed a cold start accessories recommendation model for telecom organization Technologies/Tools: Python, Knn, pandas, numpy and matplotlib Domain: Telecom / Sales

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Tools

PyCharm

Personalized accessories recommendation model

Company

Personalized accessories recommendation model

Description

Individual Contibutor

Developed a personalized accessories recommendation model for telecom organization Technologies/Tools: Python, Kmeans, pandas, numpy and matplotlib Organization: HCL Technologies Domain: Telecom / Sales

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Tools

PyCharm

Text classification (natural language processing) by using transfer learning of google pre trained word2vec (GoogleNews-vectors-negative300) model

Company

Text classification (natural language processing) by using transfer learning of google pre trained word2vec (GoogleNews-vectors-negative300) model

Description

Individual Contributor

Working on text classification (natural language processing) by using transfer learning of google pre trained word2vec (GoogleNews-vectors-negative300) model. Technologies/Tools: Keras, CNN, LSTM, Python, pandas, numpy, word embedding, nlp. Domain: Telecom / Sales

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Tools

PyCharm

Bugs Prediction in Software

Company

Bugs Prediction in Software

Description

Developed a regression model by using random forest regression of h2o to predict number of bugs in software in production. Able to achieved around 0.83 r squared.

Technologies/Tools: h20, distributed random forest regression, steam, R.

Domain: Software

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Tools

PyCharm

Mobile Propensity Model

Company

Mobile Propensity Model

Description

Developed a classification model to predict the customers who can upgrade mobile.

Able to achieved 79?curacy. We have used GBM of h2o.

Technologies/Tools: h20, GBM, steam, python, pandas, numpy, SMOTE.

Domain: Telecom /Sales

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Tools

PyCharm

Hepatitis C disease recurrence model

Company

Hepatitis C disease recurrence model

Description

Developed a classification model to predict the recurrence of hepatitis C disease after the    completion of treatment.  Able to achieved the accuracy of 91%. We have used ensemble learning by using random forest, GBM and SVM.

Technologies/Tools: R, SMOTE, ensemble learning, random forest, gbm, svm, baruta, pca, caret

Domain: Pharmaceuticals

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Tools

PyCharm

Optimization of MBI algorithm

Company

Optimization of MBI algorithm

Description

Developed a classification model to reduce the false positive instances MBI algorithm. Able to reduce the false positive cases by 7%. We have fine-tuned the already used random forest and by using various techniques of variable selection.

Technologies/Tools: R, baruta, leaps, pca, SMOTE, under sampling, logistic regression, random forest, svm, gbm

Domain: Pharmaceuticals

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Tools

PyCharm

Association rule mining model

Company

Association rule mining model

Description

Developed an association rule mining model to find patterns in the variables - which accident conditions frequently occur together.  We have used apriori algorithm of R.

Technologies/Tools: R, apriori

Domain: Insurance

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Tools

PyCharm

Sentiment analysis model

Company

Sentiment analysis model

Description

Developed a sentiment analysis model for comments written by employee in yearly engagement survey. This is polarity based model to classify the comments in Highly Positive, Positive, Neutral, Negative and Highly Negative.

Technologies/Tools: Python, VADER

Domain: HR

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Tools

PyCharm

Vehicle Emission Prediction

Company

Vehicle Emission Prediction

Description

Developed a regression model to predict the emission of various cars as per Environmental Protection Agency (EPA).  Able to achieved the accuracy of 78%. We have used ridge regression of R.

Technologies/Tools:  R, ridge regression

Domain: Automobiles

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Tools

PyCharm

Prospective Bank Customer Prediction Model

Company

Prospective Bank Customer Prediction Model

Description

Developed classification model to predict whether person can be prospective Bank Customer. Able to achieved the accuracy of 79%. We have random forest of R and also used clustering to get better prediction.

Technologies/Tools:  R, SMOTE, K-means, random forest

Domain: Banking

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Tools

PyCharm