giginghn

giginghn's Stars

• donnemartin/data-science-ipython-notebooks

  Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.

  Language:Python27.4k1.6k417.9k

• eugeneyan/applied-ml

  📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.

  27.2k949243.7k

• datasciencemasters/go

  The Open Source Data Science Masters

  24.9k1.6k566.2k

• visenger/awesome-mlops

  A curated list of references for MLOps

  12.6k396151.9k

• rapidsai/cuml

  cuML - RAPIDS Machine Learning Library

  Language:C++4.2k742.5k527

• sathishvj/awesome-gcp-certifications

  Google Cloud Platform Certification resources.

  4k210131.4k

• kojino/120-Data-Science-Interview-Questions

  Answers to 120 commonly asked data science interview questions.

  3.7k12841.3k

• spotify/chartify

  Python library that makes it easy for data scientists to create charts.

  Language:Python3.5k8875323

• DP-3T/documents

  Decentralized Privacy-Preserving Proximity Tracing -- Documents

  Language:Shell2.2k144281180

• rstudio/blogdown

  Create Blogs and Websites with R Markdown

  Language:R1.7k72604333

• JifuZhao/DS-Take-Home

  My solution to the book A Collection of Data Science Take-Home Challenges

  Language:Jupyter Notebook1.7k391861

• andrewgbruce/statistics-for-data-scientists

  Code and data associated with the book "Statistics for Data Scientists: 50 Essential Concepts"

  Language:R1.1k10210653

• 8080labs/ppscore

  Predictive Power Score (PPS) in Python

  Language:Python1.1k2762164

• ashishpatel26/Amazing-Feature-Engineering

  Feature engineering is the process of using domain knowledge to extract features from raw data via data mining techniques. These features can be used to improve the performance of machine learning algorithms. Feature engineering can be considered as applied machine learning itself.

  Language:Jupyter Notebook658151257

• rapidsai/notebooks

  RAPIDS Sample Notebooks

  Language:Shell578290199

• DP-3T/dp3t-app-android-demo

  The DP3T-App for Android

  Language:Java323473779

• zenml-io/mlstacks

  A series of Terraform based recipes to provision popular MLOps stacks on the cloud.

  Language:HCL24762532

• kellypeng/scentmate_rec

  Built a fragrance recommender using multiple machine learning algorithms to help people find their perfect match. The final deliverable was a webapp.

  Language:Jupyter Notebook1109137

• andrie/gcalendr

  R package to read events from google calendar

  Language:R5621417

• anurag-code/Survival-Analysis-Intuition-Implementation-in-Python

  Quick Implementation in python

  Language:Jupyter Notebook534153

• convoyinc/abayes

  Simulate Bayesian A/B testing algorithms and evaluate the results of A/B tests with a shiny app.

  Language:R21908

• HaminKo/SQLZoo-Solutions

  My answers to the assessments available on http://sqlzoo.net/

  Language:PLpgSQL161214

• MMBazel/Predicting-Kickstarter-Campaign-Outcomes-Using-NLP-Feature-Engineering

  Turning raw kickstarter text data => Campaign predictions using SpaCy, Scikit-learn, SQLAlchemy, SQLite3 & XGBoost Classifier (feat eng = Bag-of-Words, Tfdvectorizer)

  Language:Jupyter Notebook16003

• ohdsi-studies/MethodsLibraryPleEvaluation

  R code used to evaluate the OHDSI Methods Library for population-level estimation

  Language:R7302

• simranvatsa/lalaland

  An R package of color palettes inspired by stills from the 2016 film "La La Land"

  Language:R500

• hadinh1306/blog-posts

  Language:Jupyter Notebook4201

• sehgalnamit/preparing-for-the-google-cloud-professional-data-engineer-exam

  3100

• PyLadies-LosAngeles/pyladies-la-website

  PyLadies Los Angeles Website

  Language:HTML2300

• giginghn/Clustering-Mixed-Data

  A repository with various methods for clustering mixed datasets in python

  Language:Jupyter Notebook1000

• giginghn/poetry

  Python dependency management and packaging made easy.

  Language:Python1000