Data Science Skills and Experience Overview
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Data Science Skills and Experience Overview

Created by
@CherishedHydrogen

Questions and Answers

What is the main focus of Agrat Mohammed's career?

  • Web development
  • Data-driven decision-making (correct)
  • Database management
  • Network security
  • Which machine learning libraries is Agrat Mohammed familiar with?

  • OpenCV, NLTK, PyTorch
  • numpy, matplotlib, Keras
  • pandas, scikit-learn, TensorFlow (correct)
  • statsmodels, seaborn, Flask
  • During his internship, what was one of Agrat Mohammed's responsibilities?

  • Developing web applications
  • Implementing data preprocessing techniques (correct)
  • Conducting user interface design
  • Managing database servers
  • What was the primary project Agrat worked on during his internship?

    <p>Development of a classification model for temporary signal obstacles</p> Signup and view all the answers

    Which of the following skills does Agrat Mohammed highlight in his summary?

    <p>High data quality assurance</p> Signup and view all the answers

    What outcome did Agrat achieve by developing and implementing predictive models?

    <p>Improved obstacle detection and enhanced traffic safety</p> Signup and view all the answers

    What is one of Agrat's strengths mentioned in his summary?

    <p>Strong analytical and problem-solving skills</p> Signup and view all the answers

    How did Agrat enhance model accuracy during his internship?

    <p>By optimizing predictive models and conducting evaluations</p> Signup and view all the answers

    What was the main objective of the Mortgage Prepayment Risk Analysis project?

    <p>To analyze mortgage prepayment risk using a predictive model</p> Signup and view all the answers

    Which tool was utilized to enhance the scalability and reliability of the web application developed?

    <p>Docker</p> Signup and view all the answers

    Which programming language is highlighted for proficiency in the skill set?

    <p>Python</p> Signup and view all the answers

    What technique was used to improve the accuracy of the deep image classifier in the Image Sentiment Classification project?

    <p>Transfer learning with ResNet50</p> Signup and view all the answers

    What is the primary purpose of developing ATS-compatible resumes using the LIM Model?

    <p>To optimize formatting and keywords for ATS parsing accuracy</p> Signup and view all the answers

    What cloud platform is mentioned in the skill set?

    <p>AWS</p> Signup and view all the answers

    Which soft skill is emphasized alongside technical abilities?

    <p>Critical thinking</p> Signup and view all the answers

    What technique was utilized for continuous monitoring of deployed models in the US Visa Prediction project?

    <p>Evendently AI</p> Signup and view all the answers

    What is the accuracy rate achieved by the predictive model utilized in the Mortgage Prepayment Risk Analysis project?

    <p>87%</p> Signup and view all the answers

    Which algorithm was used in the product recommendations project to suggest visually similar products?

    <p>K-Nearest Neighbors</p> Signup and view all the answers

    During which period did the individual serve as a Machine Learning Intern?

    <p>07/2023 - 09/2023</p> Signup and view all the answers

    In the image super resolution project, what was the main application of the high-resolution images?

    <p>Surveillance for facial recognition and identification</p> Signup and view all the answers

    What challenge did the image super resolution project aim to tackle when recovering high-resolution images?

    <p>Low-resolution inputs, blur, and noise</p> Signup and view all the answers

    What was one significant feature of the content-based recommendation system developed in the product recommendations project?

    <p>It leveraged item descriptions without user profile data</p> Signup and view all the answers

    Study Notes

    Professional Summary

    • Junior Data Scientist with a strong focus on machine learning, predictive modeling, and statistical analysis.
    • Proficient in Python; experienced with ML libraries like pandas, scikit-learn, and TensorFlow.
    • Committed to improving business efficiency through predictive analytics and ensures data quality and documentation.

    Professional Experience

    • Capgemini Engineering (Internship)

      • Developed a classification model for identifying temporary signal obstacles.
      • Applied data preprocessing to clean and improve raw data quality.
      • Enhanced obstacle detection accuracy through advanced classification algorithms.
      • Deployed models using Glyphwork NCode software, documenting workflows and collaborating with Signal Processing teams.
    • Technocolabs Softwares (Internship)

      • Created a predictive model using XGBoost Classifier for mortgage prepayment risk, achieving an accuracy of 87%.
      • Developed a web application on AWS EC2 for accessible risk assessment, utilizing Docker for scalability.
      • Worked with an international team, promoting effective collaboration and knowledge sharing.

    Education

    • ENSAM Casablanca

      • Pursuing an Engineering Degree in Artificial Intelligence and Computer Science (2021-2024).
    • CPGE Meknes

      • Completed preparatory classes in Mathematics and Physics (2018-2021).

    Skills

    • Programming Languages: Proficient in Python.
    • Machine Learning & Deep Learning: Experienced with scikit-learn, TensorFlow, and other libraries for NLP, image processing, and more.
    • Data Science & Modeling: Competent in predictive modeling, statistical analysis, and model evaluation.
    • Database Management: Knowledgeable in both relational and non-relational databases.
    • Data Visualization Tools: Familiar with Power BI, Matplotlib, and Plotly.
    • Cloud Platforms Expertise: Experience with AWS, CI/CD, Docker, and version control (Git/Github).
    • Soft Skills: Strong problem-solving abilities, critical thinking, teamwork, creativity, and communication.

    Projects

    • Image Sentiment Classification

      • Conducted image data collection via web scraping; created a deep image classifier with Keras and TensorFlow, improving accuracy from 52% to 82% using transfer learning.
    • Resume Application Tracking System (ATS)

      • Developed resumes compatible with ATS using the LIM Model, focusing on optimizing formatting and keyword placements.
    • US Visa Prediction

      • Designed end-to-end ML pipelines incorporating Evendently AI for real-time model monitoring and performance tracking.
    • Product Recommendations

      • Built a content-based recommendation system using KNN algorithms to suggest similar products based on features, independent of user data.
    • Image Super Resolution using Autoencoders

      • Improved image resolution for surveillance purposes, enhancing facial recognition capabilities from low-resolution inputs.

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    Description

    Assess your knowledge and understanding of key data science skills and experiences outlined in this summary. The quiz covers machine learning techniques, tools like Python, and practical applications from data science internships. Test your ability to identify important concepts in predictive modeling and statistical analysis.

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