Alternatives and similar repositories for Data_Science_Fundamentals

Users that are interested in Data_Science_Fundamentals are comparing it to the libraries listed below

• ikding / pycon_time_series
  PyCon 2017 tutorial on time series analysis
  ☆72Updated 8 years ago
• harnav / pydata-docker-tutorial
  Tutorial given at PyData LA 2018
  ☆97Updated last year
• amueller / ml-training-advanced
  Materials for the "Advanced Scikit-learn" class in the afternoon
  ☆165Updated 6 years ago
• WillKoehrsen / probabilistic-programming
  Experimenting with and teaching probabilistic programming
  ☆105Updated 3 years ago
• ritchieng / machine-learning-nanodegree
  Codes, notes and guides on Udacity's machine learning nanodegree.
  ☆81Updated 9 years ago
• bgweber / DS_Production
  ☆155Updated 5 years ago
• khanhnamle1994 / applied-machine-learning
  A step-by-step guide to get started with Applied Machine Learning
  ☆140Updated 7 years ago
• albahnsen / PracticalMachineLearningClass
  ☆91Updated 5 years ago
• FavioVazquez / ODSC_India_2018
  My presentation at ODSC India 2018 about Deep Learning with Apache Spark
  ☆27Updated 7 years ago
• amueller / ml-workshop-4-of-4
  Advanced Machine Learning with Scikit-learn part II
  ☆163Updated 5 years ago
• rasbt / data-science-tutorial
  Code material for a data science tutorial
  ☆197Updated 8 years ago
• amueller / ml-workshop-3-of-4
  Advanced Machine Learning with Scikit-learn part I
  ☆143Updated 5 years ago
• jem1031 / pandas-pipelines-custom-transformers
  Material for Talk at PyData Seattle 2017
  ☆168Updated 7 years ago
• docker-for-data-science / docker-for-data-science-tutorial
  Materials for "Docker for Data Science" tutorial presented at PyCon 2018 in Cleveland, OH
  ☆157Updated 5 years ago
• FavioVazquez / kaggle-learning
  Repository for sharing the knowledge from the learning path of Kaggle Learning. All contributions welcome :).
  ☆153Updated 7 years ago
• amueller / talks_odt
  Slides and materials for most of my talks by year
  ☆92Updated 2 years ago
• DeltaAnalytics / machine_learning_resources
  Delta believes in building technical capacity all over the world. We believe that data is powerful, and that anybody should be able to ha…
  ☆25Updated 7 years ago
• amueller / aml
  Applied Machine Learning with Python
  ☆80Updated last year
• woobe / h2o_tutorials
  Slides and code examples for H2O tutorials at various events
  ☆56Updated 8 years ago
• amitkaps / full-stack-data-science
  Full Stack Data Science in Python
  ☆257Updated 7 years ago
• CristiVlad25 / ml-sklearn
  Tutorials on Machine Learning with Scikit-Learn
  ☆83Updated 5 years ago
• AlexIoannides / ml-workflow-automation
  Python Machine Learning (ML) project that demonstrates the archetypal ML workflow within a Jupyter notebook, with automated model deploym…
  ☆64Updated 2 years ago
• WillKoehrsen / data-science-for-good
  Data Science for Good Projects
  ☆50Updated 7 years ago
• kirit93 / NumpyTutorial
  Notebooks for tutorial on Numpy.
  ☆59Updated 5 years ago
• treselle-systems / customer_churn_analysis
  In the customer management lifecycle, customer churn refers to a decision made by the customer about ending the business relationship. It…
  ☆61Updated 2 years ago
• ankit-rathi / Data-Science-with-Python
  ☆33Updated last year
• MaartenGr / ML-API
  Guide on creating an API for serving your ML model
  ☆66Updated 3 years ago
• ethen8181 / Business-Analytics
  Data Analytics, Statistics, Visualization (R / Python)
  ☆94Updated 8 years ago
• amueller / scipy-2018-sklearn
  Scipy 2018 scikit-learn tutorial by Guillaume Lemaitre and Andreas Mueller
  ☆248Updated 7 years ago
• ritchieng / pandas-guides
  Detailed notes and codes on learning pandas quickly for machine learning.
  ☆27Updated 9 years ago