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DalyaLami/README.md

Hi 👋, I'm Dalya Lami

A passionate data analyst from Canada

I've recently graduated from the UFT Bootcamp for Data Analytics. Passionate about harnessing the power of data to derive meaningful insights and drive informed decision-making, I've embarked on a journey to explore the vast landscape of data analytics.While I'm just beginning my professional journey, I've already gained hands-on experience working on various data projects during my time at the bootcamp. From cleaning and preprocessing data to performing exploratory data analysis and creating insightful visualizations, I'm eager to apply my skills in real-world scenarios.

dalyalami

DalyaLami's GitHub | Stats

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dalya lami

Languages and Tools:

d3js illustrator javascript mysql photoshop postgresql python

dalyalami

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  1. Movie_Recomendation Movie_Recomendation Public

    Forked from DayanaIm/Movie-Recomendation-Project-4

    We are focused on developing a movie recommendation model that incorporates user ratings to provide personalized recommendations.

    Jupyter Notebook 1

  2. Exploring_the_Spectrum_of_Suicide_Rates Exploring_the_Spectrum_of_Suicide_Rates Public

    Forked from DayanaIm/Creating-Interactive-Visualizations-For-Suicide-Rates-Analysis

    Explore the various factors that influence suicide rates, such as the impact of suicide prevention and support organizations, geographical variations, the interplay of age groups and generational f…

    Jupyter Notebook 1

  3. Crowdfunding_ETL Crowdfunding_ETL Public

    Forked from DayanaIm/Crowdfunding_ETL

    Build an ETL pipeline using Python and Pandas to extract and transform the data then create CSV files and use them to create an ERD and a table schema in order to use Postgres to create tables and…

    Jupyter Notebook 1

  4. Exploring_Suicide_Rates_and_Factors Exploring_Suicide_Rates_and_Factors Public

    Forked from DayanaIm/Suicide-Rates-Analysis

    This research project seeks to comprehensively investigate suicide rates and their underlying factors over the period from 1985 to 2020.

    Jupyter Notebook 1