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Learning Machine Learning Engineer and MLOps
🏠
Learning Machine Learning Engineer and MLOps
8 followers · 6 following

Achievements

Achievement: QuickdrawAchievement: Pull Shark

Achievements

Achievement: QuickdrawAchievement: Pull Shark

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mathewsrc/README.md

Hi there 👋

Welcome to my GitHub profile! I'm Matheus, a passionate Machine Learning Engineer student.

About Me

  • 🔭 I’m currently working on projects related to machine learning, MLOps and Cloud (AWS, Azure)
  • 🌱 I’m currently learning MLOps, FastAPI, AWS, Terraform
  • I have a degree in biomedical sciences (Yes, I didn't start in the data area 😊)
  • I am currently a computer science student
  • I have MBA in data sciences
  • I'm transitioning into the data field specifically into the machine learning engineering field
  • I am looking for opportunities as a junior machine learning engineer or intern

Connect with Me

Achievements

Santander Bootcamp Scholarship 2022 (Android development) - DIO

AWS Machine Learning Engineer Scholarship 2022/2023 - Udacity

Skills

  • Programação: Python (Pandas, Matplotlib, Polars, Pyspark, Spark SQL), SQL, DuckDB
  • Aprendizado de Máquina: Scikit-learn, MLflow, Hugging Face, Optuna, Gensim, Evidentlyai
  • Nuvem: AWS (SageMaker, Lambda, S3, EC2, Step Functions, ECR, ECS, Bedrock), GCP (BigQuery), Azure (Container Registry, Container Apps)
  • Business Intelligence: Microsoft Power BI, Looker
  • ETL: Airflow, Soda
  • Containers: Docker
  • Web Scraping: Selenium e BeautifulSoup
  • Version Control: Git
  • Code as infrastructure: Terrafom
  • CI/CD: GitHub Actions
  • Microservices: FastAPI

Projects

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Most languages used

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GitHub Stats

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Feel free to explore my repositories and reach out to me. I'm always open to interesting conversations and collaborations!

Popular repositories Loading

  1. generativeai-questions-and-answers-app generativeai-questions-and-answers-app Public

    Question and Answer application using AWS Bedrock, AWS ECS, Langchain, Qdrant, and FastAPI

    HCL 14

  2. Operationalizing-an-AWS-ML-Project Operationalizing-an-AWS-ML-Project Public

    This project SageMaker features to adjust, improve, configure, and prepare a image classification model for production-grade deployment.

    Jupyter Notebook 5 1

  3. ETL-Chicago-Cafe-Permits ETL-Chicago-Cafe-Permits Public

    This ETL (Extract, Transform, Load) project employs several Python libraries, including Airflow, Soda, Polars, YData Profiling, DuckDB, Requests, Loguru, and Google Cloud to streamline the extracti…

    HTML 5 1

  4. machine-failure-prediction machine-failure-prediction Public

    Predicting machine failure

    Jupyter Notebook 3

  5. Topic-Modeling-Reclame-Aqui Topic-Modeling-Reclame-Aqui Public

    Comparison of Topic Modeling Approaches on Complaints Related to the E-Commerce Industry

    HTML 1

  6. Fine-Tuning-Pretrained-Image-Classification-Model-with-AWS-SageMaker-and-TensorFlow Fine-Tuning-Pretrained-Image-Classification-Model-with-AWS-SageMaker-and-TensorFlow Public

    Use AWS SageMaker to finetune a pretrained model that can perform image classification

    Jupyter Notebook 1