Alternatives and similar repositories for academic_advisory:

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

• szilard / teach-data-science-UCLA-master-appl-stats
  Materials for STATS 418 - Tools in Data Science course taught in the Master of Applied Statistics at UCLA
  ☆135Updated 7 years ago
• harnav / pydata-docker-tutorial
  Tutorial given at PyData LA 2018
  ☆97Updated 8 months ago
• Dpananos / GetCards
  Notebook to download machine learning flashcards
  ☆456Updated 4 years ago
• bgweber / DS_Production
  ☆154Updated 4 years ago
• amueller / ml-workshop-1-of-4
  Introduction to Machine learning with Python, 4h interactive workshop
  ☆310Updated 5 years ago
• davidyakobovitch / data_science_resources
  📊 Data Science Resources, Data Science Standards & Machine Learning Pipelines
  ☆159Updated 2 years ago
• reshamas / ds_resources
  Data Science Resources
  ☆79Updated 3 weeks ago
• amueller / ml-workshop-4-of-4
  Advanced Machine Learning with Scikit-learn part II
  ☆163Updated 5 years ago
• amueller / COMS4995-s20
  COMS W4995 Applied Machine Learning - Spring 20
  ☆245Updated 3 years ago
• jphall663 / GWU_data_mining
  Materials for GWU DNSC 6279 and DNSC 6290.
  ☆238Updated 10 months ago
• cs109 / 2018-cs109b
  Harvard CS109b Public Repository
  ☆234Updated 4 years ago
• dpressel / dliss-tutorial
  Tutorial for International Summer School on Deep Learning, 2019
  ☆317Updated 3 years ago
• DeltaAnalytics / machine_learning_for_good
  Machine learning fundamentals lesson in interactive notebooks
  ☆178Updated 4 years ago
• amitkaps / full-stack-data-science
  Full Stack Data Science in Python
  ☆257Updated 7 years ago
• FilippoBovo / production-data-science
  Production Data Science: a workflow for collaborative data science aimed at production
  ☆453Updated 4 years ago
• sharpest-minds / hiring-tips
  Compendium of tips to help you apply to machine learning and data science jobs.
  ☆52Updated 5 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
  ☆154Updated 4 years ago
• amueller / scipy-2018-sklearn
  Scipy 2018 scikit-learn tutorial by Guillaume Lemaitre and Andreas Mueller
  ☆248Updated 6 years ago
• shik3519 / programming-concepts-for-data-science
  Basics of programming: algorithms, data structures, object oriented programming
  ☆93Updated 6 years ago
• rasbt / stat479-machine-learning-fs18
  Course material for STAT 479: Machine Learning (FS 2018) at University Wisconsin-Madison
  ☆492Updated 6 years ago
• robert8138 / deep-learning-deliberate-practice
  Deliberate Practice for Learning Deep Learning
  ☆109Updated 6 years ago
• amueller / ml-workshop-3-of-4
  Advanced Machine Learning with Scikit-learn part I
  ☆142Updated 5 years ago
• rasbt / stat479-machine-learning-fs19
  Course material for STAT 479: Machine Learning (FS 2019) taught by Sebastian Raschka at University Wisconsin-Madison
  ☆734Updated 4 years ago
• LeiG / Applied-Predictive-Modeling-with-Python
  A collection of notebook to learn the Applied Predictive Modeling using Python.
  ☆275Updated 8 years ago
• rickwierenga / MLFundamentals
  Notebooks for the "ML from the Fundamentals" series
  ☆63Updated 4 years ago
• amueller / ml-training-advanced
  Materials for the "Advanced Scikit-learn" class in the afternoon
  ☆165Updated 6 years ago
• bgweber / StartupDataScience
  ☆292Updated 5 years ago
• chrispaulca / waterfall
  An easy to use waterfall chart function for Python
  ☆162Updated 4 years ago
• jem1031 / pandas-pipelines-custom-transformers
  Material for Talk at PyData Seattle 2017
  ☆168Updated 7 years ago
• dziganto / Data_Science_Fundamentals
  ☆102Updated 6 years ago