diff --git a/README.md b/README.md index b718c06..c4ec9ff 100644 --- a/README.md +++ b/README.md @@ -3,48 +3,39 @@ List of online courses I've completed, including notes and projects. - TODO: [A practical guide to Kubernetes](https://www.educative.io/module/a-practical-guide-to-kubernetes) -- [AWS Certified Solutions Architect](https://github.com/cgebbe/aws_certificates) -- [Data Engineer Nanodegree by Udacity](https://github.com/cgebbe/udacity_data_engineer) -- [Udemy NoCode courses (bubble, zapier, figma, etc.)](https://github.com/cgebbe/nocode_information) -- [Grokking Modern System Design Interview (no notes)](https://www.educative.io/courses/grokking-modern-system-design-interview-for-engineers-managers) -- [Cloud DevOps Engineer Nanodegree by Udacity](https://github.com/cgebbe/course_udacity_cloud_devops) -- [Machine Learning Engineering for Production by Coursera](https://github.com/cgebbe/coursera_mlops_specialization) -- [AWS Cloud Technical Essentials by Coursera](https://github.com/cgebbe/course_aws_cloud_technical_essentials) -- [Spark and Python for Big Data with PySpark by Udemy](https://github.com/cgebbe/course_pyspark_bigdata_udemy) -- [SQL for Data Science by Coursera](https://github.com/cgebbe/course_sql_for_data_science) -- [Full Stack Deep Learning by UC Berkley](https://github.com/cgebbe/course_full_stack_deep_learning) -- [How to win a data science competition by Coursera](https://github.com/cgebbe/coursera_win_competition) -- [Robotics: Perception by Coursera](https://github.com/cgebbe/coursera_robotics_perception) -- [Self-Driving Car Engineer Nanodegree by Udacity](https://cgebbe.github.io/udacity_nanodegree_selfdriving) - -# Original Code - -Examples of publicly available code I've written. - -## Python libraries - -- [Elliptio: Saving files to a data lake with reproducibility and metadata](https://github.com/cgebbe/elliptio_data_lake) -- [Cachephant: Caching function output to disk](https://github.com/cgebbe/cachephant) -- [Beardataclass: Converting between Dataclasses and Dataframes](https://github.com/cgebbe/beardataclass) - -## Data Science Projects - -- [Clustering job postings using BERT embeddings](https://cgebbe.medium.com/clustering-job-postings-by-skills-b33e0ad579ff) -- [Predicting future sales (Kaggle)](https://github.com/cgebbe/kaggle_predict_future_sales) -- [Detecting cars and their 3D pose in 2D images (Kaggle)](https://github.com/cgebbe/kaggle_pku-autonomous-driving) -- [Understanding Bayes, Kalman and particle filter](https://github.com/cgebbe/demo_kalman) -- [Estimating a 3D world from 2D RGB images using SLAM and OpenCV](https://github.com/cgebbe/demo_slam) -- [Understanding the optimization algorithm ADAM](https://github.com/cgebbe/demo_optimizer) - -## Sandboxes - -- [Syncing local code to Kaggle (enefit energy prediction challenge)](https://github.com/cgebbe/kaggle_enefit_predict_energy) -- [Deploying an ML model with a REST API to AWS Lambda](https://github.com/cgebbe/prototype_aws_lambda) -- [Developing inside (Kaggle) docker containers (ventilator pressure prediction challenge)](https://github.com/cgebbe/kaggle_ventilator_pressure) -- [Identifiying named entities including entity-links using Huggingface](https://github.com/cgebbe/prototype_relation_extraction) -- [Deploying a FastAPI or Streamlit App to Heroku](https://github.com/cgebbe/prototype_heroku_streamlit) -- [Transferring an image style according to Gatys et al. using PyTorch](https://github.com/cgebbe/demo_style_gatys) -- [~150 solved problems in leetcode](https://leetcode.com/cgebbe/) +- [2023 AWS Certified Solutions Architect](https://github.com/cgebbe/aws_certificates) +- [2023 Data Engineer Nanodegree by Udacity](https://github.com/cgebbe/udacity_data_engineer) +- [2023 Udemy NoCode courses (bubble, zapier, figma, etc.)](https://github.com/cgebbe/nocode_information) +- [2023 Grokking Modern System Design Interview (no notes)](https://www.educative.io/courses/grokking-modern-system-design-interview-for-engineers-managers) +- [2022 Cloud DevOps Engineer Nanodegree by Udacity](https://github.com/cgebbe/course_udacity_cloud_devops) +- [2022 Machine Learning Engineering for Production by Coursera](https://github.com/cgebbe/coursera_mlops_specialization) +- [2022 AWS Cloud Technical Essentials by Coursera](https://github.com/cgebbe/course_aws_cloud_technical_essentials) +- [2022 Spark and Python for Big Data with PySpark by Udemy](https://github.com/cgebbe/course_pyspark_bigdata_udemy) +- [2022 SQL for Data Science by Coursera](https://github.com/cgebbe/course_sql_for_data_science) +- [2021 Full Stack Deep Learning by UC Berkley](https://github.com/cgebbe/course_full_stack_deep_learning) +- [2021 How to win a data science competition by Coursera](https://github.com/cgebbe/coursera_win_competition) +- [2020 Robotics: Perception by Coursera](https://github.com/cgebbe/coursera_robotics_perception) +- [2019 Self-Driving Car Engineer Nanodegree by Udacity](https://cgebbe.github.io/udacity_nanodegree_selfdriving) + +# Code examples + +Examples of publicly available code I've written (:book:=library, :test_tube:=data science, :robot:=experiments) + +- [2024 :book: Elliptio: Saving files to a data lake with reproducibility and metadata](https://github.com/cgebbe/elliptio_data_lake) +- [2024 :book: Cachephant: Caching function output to disk](https://github.com/cgebbe/cachephant) +- [2024 :robot: Syncing local code to Kaggle (enefit energy prediction challenge)](https://github.com/cgebbe/kaggle_enefit_predict_energy) +- [2024 :book: Beardataclass: Converting between Dataclasses and Dataframes](https://github.com/cgebbe/beardataclass) +- [2022 :robot: Deploying an ML model with a REST API to AWS Lambda](https://github.com/cgebbe/prototype_aws_lambda) +- [2022 :test_tube: Identifiying named entities including entity-links using Huggingface](https://github.com/cgebbe/prototype_relation_extraction) +- [2022 :robot: Deploying a FastAPI or Streamlit App to Heroku](https://github.com/cgebbe/prototype_heroku_streamlit) +- [2021 :test_tube: Clustering job postings using BERT embeddings](https://cgebbe.medium.com/clustering-job-postings-by-skills-b33e0ad579ff) +- [2021 :robot: Developing inside (Kaggle) docker containers (ventilator pressure prediction challenge)](https://github.com/cgebbe/kaggle_ventilator_pressure) +- [2021 :test_tube: Predicting future sales (Kaggle)](https://github.com/cgebbe/kaggle_predict_future_sales) +- [2020 :test_tube: Understanding Bayes, Kalman and particle filter](https://github.com/cgebbe/demo_kalman) +- [2020 :test_tube: Estimating a 3D world from 2D RGB images using SLAM and OpenCV](https://github.com/cgebbe/demo_slam) +- [2020 :test_tube: Understanding the optimization algorithm ADAM](https://github.com/cgebbe/demo_optimizer) +- [2020 :robot: Transferring an image style according to Gatys et al. using PyTorch](https://github.com/cgebbe/demo_style_gatys) +- [2019 :test_tube: Detecting cars and their 3D pose in 2D images (Kaggle)](https://github.com/cgebbe/kaggle_pku-autonomous-driving) # Books