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lab-canvas-flappybirds's Introduction

Hey! It's Alberte.

I am a passionate full-stack developer with a growing fascination for data-related projects. Beyond functionality, I place a special emphasis on the attention to detail and the aesthetic aspect of my work. I believe that a well-designed user interface and a seamless user experience are crucial for the success of any project.

// Full-stack Knowledge
const technologies = [
  "HTML", "CSS", "Sass", "JavaScript", "Three JS", "React", "Astro", "MongoDB", "Express"
];

// Iterate over the array and display each technology
technologies.map((technology) => {
  console.log(`I love working with ${technology}! ๐Ÿ’ป๐Ÿš€`);
});

HTML CSS Sass JavaScript Three JS React Astro MongoDB Express JS


Recently, my curiosity to uncover insights through data led me to dive into the world of data. I've completed different courses on data analysis, statistics, and machine learning, and be applying these newfound skills in projects requiring deep analysis and data visualization to make informed decisions.

# Technical Knowledge
technologies = [
    'Excel', 'Tableau', 'Power BI', 'Azure', 'My SQL', 'Python', 'Numpy', 'Pandas', 'Matplotlib', 'Plotly', 'scikit-learn', 'SciPy', 'Tensorflow', 'Keras', 'R', 'Streamlit', 'Shiny for Python',
    'Supervised Learning', 'Unsupervised Learning', 'Reinforcement Learning'
]

# Iterate over the list of technologies
for tech in technologies:
    if tech in ['Supervised Learning', 'Unsupervised Learning', 'Reinforcement Learning']:
        # Print a message for machine learning concepts
        print(f"I'm also skilled in {tech} ๐Ÿค–๐Ÿ“Š")
    else:
        # Print a message for data analysis technologies
        print(f"I love working with {tech}! ๐Ÿ’ป๐Ÿš€")

Excel Tableau Power BI Azure MySQL Python NumPy Pandas Matplotlib Plotly scikit-learn SciPy TensorFlow Keras R Streamlit




lab-canvas-flappybirds's People

Contributors

papuarza avatar sandrabosk avatar

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