• Machine Learning algorithms (regression, Classification, Clustering, Dimensionality Reduction)
• Deep Learning (Generative, Adversarial, Autoencoders, LSTM networks)
• Generate reports, data analysis, and data visualizations ad-hoc (SQL, Dash, R, Python Libraries).
• Data analysis and dashboard creation.
• Consumer Behavior Analysis (A/B Testing, Risk Assessment, Market Segmentation)
• Product Testing and Quality Control
• Predictive Analytics
• Decision Making and Product Portfolio Optimization
• Product development (software, web pages, and consumer goods)

Please use use CTRL+click to open these links in a new tab 😜 _{Note: Apps on render can take up to 30-60 seconds to Load 🥺}

• Supermarket Sales Dashboard: Predicting and visualizing Metrics of Myanmar HUB

  _{🤖⚙️ A Dynamic Dash App on Render of a Dashboard for Sales and Rating Prediction}

  • _{↘️ Repository: Supermarket Sales Dashboard: Predicting and visualizing Metrics of Myanmar HUB}

• Market Watch: Dynamic Stock Tracker _{🤖⚙️ A Dynamic Dash App on Render to fetch and visualize stocks Data}

  • _{↘️ Repository: Market Watch: Dynamic Stock Tracker}

• Algorithmic Trading using LSTMs with Markowitz Portfolios _{📄 Published Article - Deep Learning}

• Energy Cost Optimization for a 4-Machine-in-sequence problem _{📄 Master's Thesis}

• Hyperparameter Optimization Techniques _{📄 Deep Learning Seminar}

• Emotions Recognition and Image Generation _{📄 Deep Learning Project}

• Linkedin

• Languages: SQL, Python, R
• Machine learning and Deep Neural Networks: Python (Tensorflow)
• Databases: MySQL, Azure, Google BigQuery
• Visualization: Tableau, Power BI, Python Libraries (Plotly/Dash, Bokeh, matplot, etc)
• Statistics: Minitab, SAS, Rstudio, Python Libraries (SciPy, Statsmodels, etc)
• Colaborative work: Miro
• Project Management tools: Jira, Zoho Projects, MS Project, Trello, MS Planner