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while alive, print: learning
🌷
while alive, print: learning
  • Singapore

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2wnh93/README.md

Hi there, I'm Zawanah 👋

I'm formerly an auditor and have since pursued my budding interest in the value and wonders of Data and Machine Learning. I am currently a Data Science Immersive Course Student at General Assembly (GA) and enjoy practising and applying knowledge I've learnt through projects and collaborating with my teammates. Python is my first language and I enjoy writing in Markdown!

🌱 Skills learnt

  • Statistics
  • Exploratory Data Analysis and Data Visualisations
  • Regression Models (Linear Regression, Multivariate Regression)
  • Classification Models (Logstic Regression, Naive Bayes, Decision Tree, Random Forest, Support Vector)
  • Feature Engineering
  • Webscraping (JSON API, Reddit API)
  • Dealing with imbalanced classes (Random Oversampling, Synthetic Minority Oversampling Technique (SMOTE), Adaptic Synthetic (ADAYSN))
  • Natural Language Processing

🐾 Recent projects

  • Solar Energy Potential Prediction
  • Credit Card Fraud Detection
  • Pricing Products (for profit maximization)
  • Reddit API and Classification
  • Predicting House Prices (Ames)
  • SAT and ACT Analysis

⚡ Fun facts

  • I have at least 2 cups/thermos with me when I work as coffee keeps my brain alert while tea prevents my brain from going on overdrive. I always have plain water with me as coffee is dehydrating and tea is a diuretic.
  • When I'm not coding, I am watching Netflix 📺, reading 📚, learning chess or I'm out and about (I love nature walks 🌿 and hikes!)

💬 Ask me about

  • my GA experience!

📫 How to reach me:

Pinned

  1. sat-act-analysis sat-act-analysis Public

    The project explores what affects SAT participation rates and recommends changes to drive higher participation rates.

    Jupyter Notebook

  2. credit-card-fraud credit-card-fraud Public

    Binary classification problem to detect fraudulent transactions. Challenges include dealing with imbalanced classes and selecting an appropriate evaluation metric.

    Jupyter Notebook

  3. pricing-products pricing-products Public

    2-step project where I first cluster (using KMeans, DBSCAN, Aggolmerative Clustering) retail transactions data. Following that, apply regression models (Lasso, ElasticNet, Ridge) to each cluster fo…

    HTML

  4. solar-power solar-power Public

    Applied clustering algorithm on 29 countries to narrow scope of analysis. Time series forecasting of solar energy potential of a country using fbprophet and neural networks.

    Jupyter Notebook

  5. web-api-and-classification web-api-and-classification Public

    The project addresses a binary classification problem (between r/Conservative and r/democrats) based on data scraped off the respective subreddits, using reddit API.

    HTML

  6. life-insurance-assessment life-insurance-assessment Public

    Multi-classification problem where the goal of the project is to determine risk level of a particular applicant based on his/her background (Eg. medical history etc.)

    Jupyter Notebook