mikiobraun / ml4tsa
Supplementary Material for Machine Learning for Time Series Analysis
☆19Updated 6 years ago
Related projects: ⓘ
- Codes related to Knocktober 2016☆23Updated 7 years ago
- Content for the Model Interpretability Tutorial at Pycon US 2019☆42Updated last month
- ☆23Updated this week
- A compiled list of kaggle competitions and their winning solutions for sequence problems.☆35Updated 8 years ago
- Notebook demonstrating use of LIME to interpret a model of long-term relationship success☆23Updated 7 years ago
- ☆22Updated last year
- PyCon 2017 tutorial on time series analysis☆72Updated 7 years ago
- Guidelines for the responsible use of explainable AI and machine learning.☆17Updated last year
- 57th place solution in "Bosch Production Line Performance"☆19Updated 7 years ago
- Presentation + Jupyter Notebook from PyGotham July 2016☆35Updated last year
- Brian Farris' Talk on Reinforcement Learning and Multi-Armed Bandits for the Data Incubator☆30Updated 6 years ago
- Python implementation of machine learning metrics☆14Updated 6 years ago
- Presentation on How to use Facebook Prophet☆8Updated 6 years ago
- Extracting LinkedIn comments from any post and export it to Excel file☆23Updated 5 years ago
- Teaching material and other info associated with the Information Extraction using Topic Models tutorial at SciPy US 2018.☆19Updated 6 years ago
- Collection of presentation of my work on various platforms and meetups☆22Updated 5 years ago
- Slides and code examples for H2O tutorials at various events☆56Updated 7 years ago
- This is a comprehensive guide on how you can automate your feature engineering process.☆11Updated 6 years ago
- Notes for Data Science 350 Class☆23Updated 7 years ago
- Sample Notebooks for PipelineAI☆44Updated last year
- Slides and materials for most of my talks by year☆91Updated last year
- Sample use case for Xavier AI in Healthcare conference: https://www.xavierhealth.org/ai-summit-day2/☆26Updated 3 months ago
- Repository for the PyData DC 2016 tutorial☆29Updated 7 years ago
- These are the slides and code for my tutorial "Computer Vision: an (Un?)Expected Journey" at PyData London 2018☆29Updated 6 years ago
- ☆21Updated 5 years ago
- Repo for the course "Fundamentals of Deep Learning with Pytorch"☆39Updated 2 years ago
- Tutorial repo for the article "ML in Production"☆30Updated last year
- Introduction to machine learning☆10Updated 6 years ago
- In-class exercises for Deep Learning course at NYC Data Science Academy☆32Updated 6 years ago
- Notebook and slides for my talk at Pydata NYC 2018☆88Updated 3 months ago