Link to the Python code for my stock price prediction web app using a deep neural network/LSTM* machine learning model
: Try my Stock Price Prediction Web App at https://mikibahng.com
Hi! I'm Mi-Kyung "Miki" Bahng.
Data Analytics/Data science/machine learning/MLOps enthusiast with diverse experience in business, marketing and sciences: Ph.D. in Physical Chemistry/Chemical Physics & MBA with a marketing research (Big Data) focus. I have built various predictive models using ML methods. My recent projects include python web apps for COVID-19 tracking, image recognition, movie recommendation, sentiment analysis, stock price prediction, etc., with some tasks automated using scripts.
Portfolio
Link to my paper @ ACS Energy & Fuel
: Click here to see the full list of my publications and presentations in PDF, or refer to the list of my publications on Google Scholar
Link to the programming codes for the simplified version of Miki Bahng's website
: Try my Google News Headline Sentiment Analysis Web App at https://mikibahng.com
Link to my R programming project, "Human Activity Recognition Using Smartphones Data Set", which was part of the Coursera Johns Hopkins Data Science Specialization.
: The report (HTML version) can be viewed here
Link to the Python code for the movie recommendation models
: Try my Movie Recommendations Web App at https://mikibahng.com
Link to my SAS machine learning project introduction
: See the SAS code for Decision Trees, Random Forest, Lasso Regression, k-means Clustering, and more at https://mikibahng.com
About Me
Data scientist / advanced analytics & marketing research professional who has over 10 years of research experience, business strategy/marketing (3+ years) & scientific research combined. I help improve strategic planning by offering insights via advanced (predictive & prescriptive) analytics and effective communications between the departments, e.g., Marketing & Sales, R&D, and IT with my in-depth understanding of business, marketing and sciences.
MBA with an emphasis in Marketing Research (Big Data)
PhD in Physical Chemistry / Chemical Physics
Extensive experience using Python, R, SAS, SPSS, SQL, MongoDB, and Tableau, including big data applications such as Databricks, Teradata and Cloudera (Hadoop / MapReduce / HBase / Hive / Pig / Spark)
Machine learning / Predictive modeling / Multivariate analysis (regression, classification, clustering, decision trees, deep neural networks, etc) experience in various applications: from predictive modeling in scientific research to advanced analytics in business applications such as customer segmentation, churn prediction, recommender systems, sentiment analysis, multivariate time-series prediction models, etc.
Certifications: Business Analytics Specialization [Customer / Operations / People / Accounting Analytics] (Wharton / University of Pennsylvania), Strategic Business / Marketing Analytics and Case Studies in Business Analytics with ACCENTURE (ESSEC Business School), Big Data Specialization (UC, San Diego), Data Science Specialization (Johns Hopkins), Data Science at Scale Specialization (University of Washington), Machine Learning Specialization (University of Washington), Excel to MySQL: Analytic Techniques for Business Specialization (Duke University), Data Warehousing for Business Intelligence courses (CU, Denver), Python Programming courses (University of Michigan), etc. via Coursera
Please, refer to my resume at mikibahng.com or Linkedin