vsmolyakov / pyspark
spark (scala and python)
☆18Updated 5 years ago
Alternatives and similar repositories for pyspark:
Users that are interested in pyspark are comparing it to the libraries listed below
- Data Science and Machine Learning with Python - Hands On from Udemy☆14Updated 7 years ago
- Code for my presentation: Using PySpark to Process Boat Loads of Data☆20Updated 7 years ago
- pyspark sample scripts☆17Updated 6 years ago
- How to do data science with Optimus, Spark and Python.☆19Updated 5 years ago
- ☆19Updated 3 years ago
- Brian Farris' Talk on Reinforcement Learning and Multi-Armed Bandits for the Data Incubator☆30Updated 6 years ago
- My work on UCSD CSE 250B Principles of Artificial Intelligence: Learning Algorithms☆13Updated 5 years ago
- ☆15Updated 2 years ago
- My presentation at ODSC India 2018 about Deep Learning with Apache Spark☆27Updated 6 years ago
- ☆26Updated last year
- Bayesian statistics seminars☆30Updated 7 years ago
- Slides and materials for most of my talks by year☆92Updated last year
- feng - feature engineering for machine-learning champions☆27Updated 7 years ago
- Model explanation provides the ability to interpret the effect of the predictors on the composition of an individual score.☆13Updated 4 years ago
- Material for UW Extension Data Science 350☆19Updated 7 years ago
- notebooks for nlp-on-spark☆13Updated 8 years ago
- 32/2384 Solution to Kaggle Mercari Competition (solo silver medal winner)☆20Updated 7 years ago
- ☆11Updated 6 years ago
- Using Luigi to create a Machine Learning Pipeline using the Rossman Sales data from Kaggle☆33Updated 8 years ago
- Hands on Unsupervised Learning with Python [Video], Published by Packt☆29Updated 2 years ago
- Kaggle competition results☆20Updated 6 years ago
- Data models, build data warehouses and data lakes, automate data pipelines, and worked with massive datasets.☆13Updated 5 years ago
- Tutorial repo for the article "ML in Production"☆30Updated 2 years ago
- Techniques & resources for training interpretable ML models, explaining ML models, and debugging ML models.☆21Updated 2 years ago
- Applying automated feature engineering to the Kaggle Home Credit Default Risk Competition☆18Updated 6 years ago
- An example of how the LIME algorithm can be used to provide real-world insight into the decision processes of a 'black-box' machine learn…☆15Updated 6 years ago
- Building an API with the FastAPI framework to serve a scikit-learn model.☆18Updated 6 years ago
- ☆15Updated 6 years ago
- Work for Mastering Large Datasets with Python☆18Updated 2 years ago
- Pyspark in Google Colab: A simple machine learning (Linear Regression) model☆36Updated 5 years ago