romikukreja

romikukreja's Stars

• donnemartin/system-design-primer

  Learn how to design large-scale systems. Prep for the system design interview. Includes Anki flashcards.

  Language:Python270k45.6k

• lukasz-madon/awesome-remote-job

  A curated list of awesome remote jobs and resources. Inspired by https://github.com/vinta/awesome-python

  29.2k3.4k

• google/eng-practices

  Google's Engineering Practices documentation

  19.9k2k

• git-duet/git-duet

  Support for pairing with git

  Language:Shell41940

• facebookresearch/SlowFast

  PySlowFast: video understanding codebase from FAIR for reproducing state-of-the-art video models.

  Language:Python6.5k1.2k

• GokuMohandas/Made-With-ML

  Learn how to design, develop, deploy and iterate on production-grade ML applications.

  Language:Jupyter Notebook37.1k5.9k

• Nextdoor/airflow

  Airflow is a system to programmatically author, schedule and monitor data pipelines.

  Language:Python75

• CamDavidsonPilon/lifetimes

  Lifetime value in Python

  Language:Python1.4k375

• ujjwalkarn/Machine-Learning-Tutorials

  machine learning and deep learning tutorials, articles and other resources

  15.3k3.8k

• rasbt/python-machine-learning-book

  The "Python Machine Learning (1st edition)" book code repository and info resource

  Language:Jupyter Notebook12.2k4.4k

• guipsamora/pandas_exercises

  Practice your pandas skills!

  Language:Jupyter Notebook10.7k8.2k

• josephmisiti/awesome-machine-learning

  A curated list of awesome Machine Learning frameworks, libraries and software.

  Language:Python65.4k14.6k

• drabastomek/learningPySpark

  Code base for the Learning PySpark book (in preparation)

  Language:Jupyter Notebook621482

• felixcheung/spark-notebook-examples

  Some notebook examples related to Apache Spark, IPython / Jupyter, Zeppelin

  Language:Jupyter Notebook5248

• GalvanizeDataScience/building-spark-applications-live-lessons

  Supporting content (slides and exercises) for the Addison-Wesley (Pearson) video series covering best practices for developing scalable Spark applications for predictive analytics in the context of a data scientist's standard workflow.

  Language:Jupyter Notebook6682

• PiercingDan/spark-Jupyter-AWS

  A guide on how to set up Jupyter with Pyspark painlessly on AWS EC2 clusters, with S3 I/O support

  Language:Jupyter Notebook26219

• jadianes/data-science-your-way

  Ways of doing Data Science Engineering and Machine Learning in R and Python

  Language:Jupyter Notebook595254

• DopplerHQ/awesome-interview-questions

  :octocat: A curated awesome list of lists of interview questions. Feel free to contribute! :mortar_board:

  70.4k8.8k