| Resume alert | Resumes 71 - 80 of 500 |
Software Developer Engineer
San Jose, CA
... The model selects the 25 most influential factors from 100 factors provided by the US Energy Department using a random forest classifier, then applies them by importance. https://github.com/Monkeyank/Residential_Electricity_Consuption_Mac ... - 2021 Feb 20
... The model selects the 25 most influential factors from 100 factors provided by the US Energy Department using a random forest classifier, then applies them by importance. https://github.com/Monkeyank/Residential_Electricity_Consuption_Mac ... - 2021 Feb 20
Data Assistant
Campbell, CA
... Using data mining method, developed and predicted the model based on random forest model with accuracy of 97.3% Software Product Process Enhancement (WonderCard): May 2020 Spearheaded Six Sigma Methodology, implementing the Water-Scrum-Fall Model to ... - 2021 Feb 02
... Using data mining method, developed and predicted the model based on random forest model with accuracy of 97.3% Software Product Process Enhancement (WonderCard): May 2020 Spearheaded Six Sigma Methodology, implementing the Water-Scrum-Fall Model to ... - 2021 Feb 02
Machine Data
Stanford, CA
... Lasso 8) Association rules mining 9) Tree/Boosting: XGBOOST, Random Forest LANGUAGE SKILLS French (Fluent), English (Fluent), Mandarin (Fluent) ACTIVITIES - INTERESTS - CERTIFICATION 1) Partner at Mythos Biotechnology Fund, a Stanford biotech fund. ... - 2021 Jan 27
... Lasso 8) Association rules mining 9) Tree/Boosting: XGBOOST, Random Forest LANGUAGE SKILLS French (Fluent), English (Fluent), Mandarin (Fluent) ACTIVITIES - INTERESTS - CERTIFICATION 1) Partner at Mythos Biotechnology Fund, a Stanford biotech fund. ... - 2021 Jan 27
Data Analyst
San Jose, CA
... ACADEMIC PROJECTS Prediction of Kickstarter projects (Random Forest, KNN, XGboost, Ensemble Techniques, NLP) • Machine learning model is built to predict whether the project would be successful or failure. • Performed Sentiment Analysis on Blurb ... - 2021 Jan 26
... ACADEMIC PROJECTS Prediction of Kickstarter projects (Random Forest, KNN, XGboost, Ensemble Techniques, NLP) • Machine learning model is built to predict whether the project would be successful or failure. • Performed Sentiment Analysis on Blurb ... - 2021 Jan 26
Customer Data
San Jose, CA
... feature transformation, and standardization ● Built supervised machine learning models including Logistic Regression, Random Forest and K-Nearest Neighbors, selected the optimal hyperparameters by regularization in each model ● Used 5-fold cross ... - 2021 Jan 25
... feature transformation, and standardization ● Built supervised machine learning models including Logistic Regression, Random Forest and K-Nearest Neighbors, selected the optimal hyperparameters by regularization in each model ● Used 5-fold cross ... - 2021 Jan 25
Machine Data
Sunnyvale, CA
... • Implemented automated anomaly detection of hospitals Neuro and Psych demand using isolation forest to identify unusual volume achieving 20% SLA improvement during COVID. Machine Learning Engineer, Yantriks LLC Aug 2018 – Dec 2018 • Implemented ATP ... - 2021 Jan 24
... • Implemented automated anomaly detection of hospitals Neuro and Psych demand using isolation forest to identify unusual volume achieving 20% SLA improvement during COVID. Machine Learning Engineer, Yantriks LLC Aug 2018 – Dec 2018 • Implemented ATP ... - 2021 Jan 24
Teaching Assistant
San Jose, CA
... o Build a non-parametric model – Quantile regression and models using advanced machine learning techniques such as Decision Tree, Random Forest, SVM, kNN and compared the different models. 3. COVID19 Xcel Energy Consumption Impact: o Analyzed the ... - 2021 Jan 21
... o Build a non-parametric model – Quantile regression and models using advanced machine learning techniques such as Decision Tree, Random Forest, SVM, kNN and compared the different models. 3. COVID19 Xcel Energy Consumption Impact: o Analyzed the ... - 2021 Jan 21
Data Analyst Python
San Jose, CA
... Identified feature dependencies to remove redundancy and applied Random forest, Naïve Bayes, to ensemble the Machine Learning models and took the maximum vote for prediction. (Fall 2020) Dashboard Visualization of Data Science Jobs, SJSU Performed ... - 2021 Jan 21
... Identified feature dependencies to remove redundancy and applied Random forest, Naïve Bayes, to ensemble the Machine Learning models and took the maximum vote for prediction. (Fall 2020) Dashboard Visualization of Data Science Jobs, SJSU Performed ... - 2021 Jan 21
Software Engineering Intern
San Jose, CA
... Created a random forest model with a mean squared error of 16.52%. The model outperformed the baseline model by 61.3%. • Receipt OCR: Designed and developed optical character recognition model which extracts data from a receipt image and store it in ... - 2021 Jan 20
... Created a random forest model with a mean squared error of 16.52%. The model outperformed the baseline model by 61.3%. • Receipt OCR: Designed and developed optical character recognition model which extracts data from a receipt image and store it in ... - 2021 Jan 20
Machine Learning Engineer
San Jose, CA
... • Modulation Prediction: Used Python with sklearn and TensorFlow to implement AdaBoost with Random Forest, CNN and ResNet to predict the signal modulation schemes. • Divorce Prediction: Used R to implement various parametric and non-parametric ... - 2021 Jan 10
... • Modulation Prediction: Used Python with sklearn and TensorFlow to implement AdaBoost with Random Forest, CNN and ResNet to predict the signal modulation schemes. • Divorce Prediction: Used R to implement various parametric and non-parametric ... - 2021 Jan 10