Most popular kaggle competition solutions
Kaggle competition solutions
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Kaggle is one of the most popular data science competitions hub. Which offers a wide range of real-world data science problems to challenge each and every data scientist in the world. These problems fall under different data science categories. These categories are like machine learning, deep learning, opinion mining, sentiment analysis and a lot more.
Every data science enthusiastic dreams to get top in kaggle leaderboard. But It’s not an easy thing to stay top on kaggle leaderboard. As the world is filled with some top mined data scientist. Who always loves to fine tune the solution with different approaches by applying different algorithms based on the problem domain.
kaggle is not only for top mined data scientists. It will also offer freedom to data science beginners a way to learn how to solve the data science problems. Beginners can learn a lot from the peer’s solutions and from the kaggle discussion forms. So in this post, we were interested in sharing most popular kaggle competition solutions. If you are pure data science beginner and admirers to test your theoretical knowledge by solving the real-world data science problems. This post will sure become your favourite one.
1.Titanic: Machine Learning from Disaster Solution:
Kaggle Titanic problem is the most popular data science problem. This is the most recommend challenge for data science beginners. The problem statement for this challenge is to predict passenger survival or not survival. To train a classification model to predict a passenger is survived or not we are giving the passenger features like gender , passenger id, the cost of the ticket ,passenger traveling class and a lot many other features.
You can find the solution for this problem in python and as well as in R programming language.
- Titanic kaggle solution in Python
- Getting started in kaggle with Python
- Titanic Kaggle solution in R
2. Allstate Purchase Prediction Challenge
All state purchase Prediction challenge is a tricky prediction problem. where we have to predict what policy will customer chooses by analysing the customer’s shopping history. The features are like customer Id, information about the customer and the information about the policy and the cost.
3. Galaxy Zoo – The Galaxy Challenge
Galaxy Zoo – The Galaxy problem was sponsored by Winton Capital. The is the most popular challenge to test your deep learning knowledge. In detail, this challenge is to classify the morphologies of distant galaxies in our universe. To solve this challenge we need understanding the distribution, location and different types of galaxies their shape, size, and color.
4. MLSP 2013 Bird Classification Challenge
Bird classification challenge is a 3-year-old problem but worth practicing. This is because of it mainly a voice-related problem where we have to predict the bird species from a given an audio clip with the length of 10 seconds. By solving this kind of problem you will get a chance to utilise both single processing and machine learning concepts.Some of the trick challenges include in solving this problem were multiple simultaneously vocalizing birds, other sources of non-bird sound (e.g. buzzing insects), and background noise like wind, rain, and motor vehicles.
5. Large Scale Hierarchical Text Classification
Large Scale Hierarchical Text Classification is a document classification challenge to classify a given Wikipedia document into one of the 325,056 categories. Wikipedia has created this very large dataset. The dataset is multi-class, multi-label and hierarchical. The numbers of categories were somewhere around 325,000 and the numbers documents size is 2,400,000.
This challenge builds upon a series of successful challenges on large-scale hierarchical text classification. Demokritos will give more information on this dataset at http://lshtc.iit.demokritos.gr/
- Large scale hierarchical text classification solution
- Large scale hierarchical text classification winner discussion
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Please let us know if we miss any popular kaggle challenge, So we will add it here.
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