glennl

glennlum

Enhancing Productivity through Automated Browser Testing with Selenium WebDriver.

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Effective Data Analysis Using NumPy and Pandas: A Python Reference Guide

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Accelerating Data Visualization with Python: Utilizing Matplotlib, Seaborn, Plotly, and Dash

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Predicting Customer Conversions from Leads Using Logistic Regression and Decision Trees.

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Automated Football Score Tracking: Using Selenium and Python Web Scraping to Identify Top Performing Teams.

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Utilizing Natural Language Processing to Analyze Sentiment Trends in Airline Customer Tweets.

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🚧 (WIP) Developing a Production-Ready ETL Pipeline for Aggregating Daily Trading Data: Implementing Best Practices in Python and Data Engineering.

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Designing a Deep Learning Model for Automated Recognition of Street View House Numbers.

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Accelerating Plant Seedling Identification and Classification Using Convolutional Neural Networks

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Utilizing Cluster Analysis on Stock Market Data to Strategically Create Diversified Investment Portfolios for Clients

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Utilizing Ensemble Techniques to Classify US Visa Applicants: Analyzing Visa Approvals and Identifying the Key Factors Influencing Case Status Outcomes

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Developing and Optimizing Classification Models to Predict Wind Turbine Generator Failures and Minimize Maintenance Costs

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Developing a Linear Regression Model to Forecast Used Phone/Tablet Prices and Analyze Influential Factors

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Exploring Uber Pickup Trends in New York City (2015): Strategies to Capitalise on Demand Fluctuations

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Analyzing an A/B test by a news site to assess if a new landing page increased customer conversion rates

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Leveraging DagsHub to Optimize a Machine Learning Model Training Pipeline with Experiment Tracking

scikit-learn dvc git