☆58Jun 19, 2021Updated 5 years ago
Alternatives and similar repositories for Titanic-Machine-Learning
Users that are interested in Titanic-Machine-Learning are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- ☆25Jun 5, 2015Updated 11 years ago
- Problem Sets for Jour72326: Scraping for Journalists.☆20May 22, 2017Updated 9 years ago
- ☆10Jan 15, 2017Updated 9 years ago
- Social Media and Text Analytics Course at UPenn☆25Apr 16, 2023Updated 3 years ago
- A Python Tour of Data Science☆30Dec 15, 2017Updated 8 years ago
- Deploy on Railway without the complexity - Free Credits Offer • AdConnect your repo and Railway handles the rest with instant previews. Quickly provision container image services, databases, and storage volumes.
- R Code + Jupyter notebook for analyzing and visualizing NYC Taxi data☆31Nov 16, 2015Updated 10 years ago
- Public code files for the DDL blog☆56Jun 6, 2018Updated 8 years ago
- R files containing the code used to predict rugby world cup matches☆11Sep 18, 2015Updated 10 years ago
- Introduction to data visualization in Python, including plotting data from NetCDF files. Originally created for a Short Course in Data As…☆49Oct 22, 2021Updated 4 years ago
- A web application that recommends songs via "country arithmetic" and hand-rolled Implicit Matrix Factorization☆10May 5, 2017Updated 9 years ago
- Using data to dig into the 2015 NL Cy Young race☆10Nov 19, 2015Updated 10 years ago
- iPython notebooks and data files for the 'Pandas in a Hurry' tutorial of the 2015 San Diego Data Science Fun Conference☆12Feb 27, 2015Updated 11 years ago
- Neural Net Starter Examples☆88Jul 4, 2015Updated 11 years ago
- A series of IPython notebooks on Python for data analysis geared towards environmental sciences☆65Apr 1, 2015Updated 11 years ago
- Virtual machines for every use case on DigitalOcean • AdGet dependable uptime with 99.99% SLA, simple security tools, and predictable monthly pricing with DigitalOcean's virtual machines, called Droplets.
- ☆10Jan 15, 2018Updated 8 years ago
- ☆66Jun 14, 2023Updated 3 years ago
- Talk on "Bayesian optimisation", beginner level☆25Apr 11, 2016Updated 10 years ago
- ☆53Sep 10, 2015Updated 10 years ago
- Interactive visualization of non-linear logistic regression decision boundaries☆28Jul 24, 2014Updated 12 years ago
- Experiments on english wikipedia. GloVe and word2vec.☆13Dec 1, 2015Updated 10 years ago
- This is the code for the "Build a Web Scraper" Live stream by @Sirajology on Youtube☆53Jan 29, 2019Updated 7 years ago
- Sequential model-based optimization with a `scipy.optimize` interface☆15Aug 3, 2017Updated 9 years ago
- ☆28Jun 6, 2016Updated 10 years ago
- Virtual machines for every use case on DigitalOcean • AdGet dependable uptime with 99.99% SLA, simple security tools, and predictable monthly pricing with DigitalOcean's virtual machines, called Droplets.
- 解构R语言中的“黑魔法”☆17Jun 11, 2015Updated 11 years ago
- Our efforts to plan reactroings in a structured way. Mainly, we apply advanced dependency analysis of source code☆13Oct 17, 2015Updated 10 years ago
- Materials for dask talk at PyData NYC☆15Nov 11, 2015Updated 10 years ago
- My 2nd place submission (working with Kevin Goetsch) out of 28 teams at the Kaggle competition at PyCon2015.☆23Apr 17, 2015Updated 11 years ago
- The notes and slides from my PyCon Ireland 2016 PyData talk an introduction to gradient boosting☆18Nov 7, 2016Updated 9 years ago
- Multilayer Neural Network using numpy.☆55Jan 12, 2017Updated 9 years ago
- The slides, code examples and resources for the PyCon 2015 Ireland talk on building data pipelines☆13Oct 26, 2015Updated 10 years ago
- Introduction to Python for Data Science☆39Nov 2, 2017Updated 8 years ago
- A fun introduction to Pandas andScikit-Learn using nfl data☆45Jan 12, 2016Updated 10 years ago
- GPU virtual machines on DigitalOcean Gradient AI • AdGet to production fast with high-performance AMD and NVIDIA GPUs you can spin up in seconds. The definition of operational simplicity.
- Talk on "Tree models with Scikit-Learn: Great learners with little assumptions" presented at PyPata Paris 2015☆50Apr 1, 2015Updated 11 years ago
- ☆42Nov 1, 2020Updated 5 years ago
- experiments with the R package TSclust☆11Mar 5, 2015Updated 11 years ago
- Materials for Data Science Journey 2018: AutoML Competition☆25Oct 25, 2018Updated 7 years ago
- Public Machine Learning and Data Competition Repo☆54Nov 20, 2015Updated 10 years ago
- Code and data for bike forecast post☆17Mar 24, 2015Updated 11 years ago
- A toolbox of functions for easier shiny development.☆12Feb 27, 2019Updated 7 years ago