Competition Libraries

6 Components & Libraries

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Competition Libraries

All Algorithms implemented in Python

Implementations are for learning purposes only. They may be less efficient than the implementations in the Python standard library. Use them at your discretion.

A tutorial for Kaggle's Titanic: Machine Learning from Disaster competition. Demonstrates basic data munging, analysis, and visualization techniques. Shows examples of supervised machine learning techniques.

This is a tutorial in an IPython Notebook for the Kaggle competition, Titanic Machine Learning From Disaster. The goal of this repository is to provide an example of a competitive analysis for those …

The projects I do in Machine Learning with PyTorch, keras, Tensorflow, scikit learn and Python.

My Projects, Kaggle Competitions and implementation of some popularly known machine learning algorithms. I have also included a list of research papers I have curated in the feild of ML/DL/AI. Follow…

My Attempt(s) In The World Of ML/DL....

Loose path: Understanding Math is pivotal. You can never be a good Machine Learning Scientistby skipping the Math. Python - Any one, both courses are equally good Algorithms Since you'll be coding a …

DATA-SCIENCE-BOWL-2018 Find the nuclei in divergent images to advance medical discovery

Imagine speeding up research for almost every disease, from lung cancer and heart disease to rare disorders. The 2018 Data Science Bowl offers our most ambitious mission yet: create an algorithm to…