Alternatives and similar repositories for industry-machine-learning:

Users that are interested in industry-machine-learning are comparing it to the libraries listed below

• kmario23 / deep-learning-drizzle
  Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lect…
  ☆12,480Updated 3 months ago
• alirezadir / Production-Level-Deep-Learning
  A guideline for building practical production-level deep learning systems to be deployed in real world applications.
  ☆4,405Updated last year
• firmai / data-science-career
  Career Resources for Data Science, Machine Learning, Big Data and Business Analytics Career Repository
  ☆949Updated 6 months ago
• r0f1 / datascience
  Curated list of Python resources for data science.
  ☆4,322Updated last month
• EthicalML / awesome-production-machine-learning
  A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
  ☆18,073Updated this week
• microsoft / nlp-recipes
  Natural Language Processing Best Practices & Examples
  ☆6,393Updated 2 years ago
• terryum / awesome-deep-learning-papers
  The most cited deep learning papers
  ☆25,690Updated last year
• kojino / 120-Data-Science-Interview-Questions
  Answers to 120 commonly asked data science interview questions.
  ☆3,757Updated last year
• rasbt / python-machine-learning-book-2nd-edition
  The "Python Machine Learning (2nd edition)" book code repository and info resource
  ☆7,145Updated 4 years ago
• jayinai / data-science-question-answer
  A repo for data science related questions and answers
  ☆2,420Updated 2 years ago
• PAIR-code / facets
  Visualizations for machine learning datasets
  ☆7,356Updated last year
• trekhleb / homemade-machine-learning
  🤖 Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained
  ☆23,299Updated 3 months ago
• ahkarami / Deep-Learning-in-Production
  In this repository, I will share some useful notes and references about deploying deep learning-based models in production.
  ☆4,319Updated 3 months ago
• Spandan-Madan / DeepLearningProject
  An in-depth machine learning tutorial introducing readers to a whole machine learning pipeline from scratch.
  ☆4,753Updated 2 years ago
• eriklindernoren / ML-From-Scratch
  Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. …
  ☆24,275Updated last year
• rushter / data-science-blogs
  A curated list of data science blogs
  ☆6,339Updated 8 months ago
• dformoso / machine-learning-mindmap
  A mindmap summarising Machine Learning concepts, from Data Analysis to Deep Learning.
  ☆6,153Updated 4 years ago
• jphall663 / awesome-machine-learning-interpretability
  A curated list of awesome responsible machine learning resources.
  ☆3,718Updated this week
• ritchieng / the-incredible-pytorch
  The Incredible PyTorch: a curated list of tutorials, papers, projects, communities and more relating to PyTorch.
  ☆11,713Updated last month
• bfortuner / ml-glossary
  Machine learning glossary
  ☆3,039Updated 6 months ago
• christophM / interpretable-ml-book
  Book about interpretable machine learning
  ☆4,837Updated 3 weeks ago
• facebook / prophet
  Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
  ☆18,866Updated 3 months ago
• microsoft / tensorwatch
  Debugging, monitoring and visualization for Python Machine Learning and Data Science
  ☆3,433Updated last year
• explosion / spacy-course
  👩‍🏫 Advanced NLP with spaCy: A free online course
  ☆2,341Updated last week
• fastai / fastai
  The fastai deep learning library
  ☆26,626Updated 2 months ago
• GokuMohandas / Made-With-ML
  Learn how to design, develop, deploy and iterate on production-grade ML applications.
  ☆38,171Updated 6 months ago
• rushter / MLAlgorithms
  Minimal and clean examples of machine learning algorithms implementations
  ☆10,789Updated last year
• donnemartin / data-science-ipython-notebooks
  Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce,…
  ☆27,855Updated 10 months ago
• ydataai / ydata-profiling
  1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.
  ☆12,723Updated this week
• interpretml / interpret
  Fit interpretable models. Explain blackbox machine learning.
  ☆6,384Updated last week