I am a newbie and have no idea how to deal with this stuff. Can someone suggest prerequisites for getting started with these contests? What should I learn to get started in minimum time? Suggest resources.
", "messages": [ { "id": "478537", "postDate": "02/26/2019 09:54:04", "content": "I am a newbie and have no idea how to deal with this stuff. Can someone suggest prerequisites for getting started with these contests? What should I learn to get started in minimum time? Suggest resources.
", "rawMarkdown": "I am a newbie and have no idea how to deal with this stuff. Can someone suggest prerequisites for getting started with these contests? What should I learn to get started in minimum time? Suggest resources.", "votes": null }, { "id": "478592", "postDate": "02/26/2019 11:21:50", "content": "To start with, go to kernel that has been created by others in 'knowledge' category. For example, 'Titanic' problem and see a kernel that has been created using a programming language that you are familiar with. Go through them line by line and try to understand what has been done.
\n\nDon't give up and go through other kernels as well which are created by others. You will slowly will get to know how to get started with these contests. There is no minimum time set by anybody and it purely depends on your dedication to learn. Hope this helps!
", "rawMarkdown": "To start with, go to kernel that has been created by others in 'knowledge' category. For example, 'Titanic' problem and see a kernel that has been created using a programming language that you are familiar with. Go through them line by line and try to understand what has been done. \n\nDon't give up and go through other kernels as well which are created by others. You will slowly will get to know how to get started with these contests. There is no minimum time set by anybody and it purely depends on your dedication to learn. Hope this helps!", "votes": null }, { "id": "478839", "postDate": "02/26/2019 17:36:21", "content": "Have a look at this discussion on an Earthquake Prediction Tutorial.
\n\nIt is important to watch the video, which is linked to on that post. But the discussion gives you an outline of the steps to follow.
", "rawMarkdown": "Have a look at this discussion on an [Earthquake Prediction Tutorial](https://www.kaggle.com/c/LANL-Earthquake-Prediction/discussion/81143). \n\nIt is important to watch the video, which is linked to on that post. But the discussion gives you an outline of the steps to follow.", "votes": null }, { "id": "480615", "postDate": "02/28/2019 12:32:55", "content": "Try to see some public kernels for this competition:\nhttps://www.kaggle.com/c/LANL-Earthquake-Prediction/kernels\nThere's a lot of them explainig what's going on general
", "rawMarkdown": "Try to see some public kernels for this competition:\nhttps://www.kaggle.com/c/LANL-Earthquake-Prediction/kernels\nThere's a lot of them explainig what's going on general", "votes": null }, { "id": "482934", "postDate": "03/03/2019 21:57:08", "content": "Hello Abhishek,
\n\nI'm relatively new to Kaggle and ML too. I found the following to be most useful in getting started (not sure of your programming experience generally, but this is what I've reviewed so far):
\n\nKaggle Learn's Micro-Courses\n- Python Overview\n- Pandas Overview\n- Machine Learning Overview (Levels 1 & 2)
\n\nUser Inversion's \"Basic Feature Benchmark\" Kernel\n- Basic Solution to LANL Earthquake Prediction
\n\nI've also found reading certain discussion board posts and kernels to be useful, but don't get too bogged down if things appear complex or foreign. It will take time..
", "rawMarkdown": "Hello Abhishek,\n\nI'm relatively new to Kaggle and ML too. I found the following to be most useful in getting started (not sure of your programming experience generally, but this is what I've reviewed so far):\n\n***Kaggle Learn's Micro-Courses***\n- [Python Overview](https://www.kaggle.com/learn/python)\n- [Pandas Overview](https://www.kaggle.com/learn/pandas)\n- [Machine Learning Overview (Levels 1 & 2)](https://www.kaggle.com/learn/machine-learning)\n\n***User Inversion's \"Basic Feature Benchmark\" Kernel***\n- [Basic Solution to LANL Earthquake Prediction](https://www.kaggle.com/inversion/basic-feature-benchmark)\n\nI've also found reading certain discussion board posts and kernels to be useful, but don't get too bogged down if things appear complex or foreign. It will take time..", "votes": null } ], "comments": [ { "id": 478592, "author_name": "mathan", "author_url": "", "post_date": "02/26/2019 11:21:50", "content": "To start with, go to kernel that has been created by others in 'knowledge' category. For example, 'Titanic' problem and see a kernel that has been created using a programming language that you are familiar with. Go through them line by line and try to understand what has been done.
\n\nDon't give up and go through other kernels as well which are created by others. You will slowly will get to know how to get started with these contests. There is no minimum time set by anybody and it purely depends on your dedication to learn. Hope this helps!
", "votes": null, "replies": [] }, { "id": 478839, "author_name": "devilears", "author_url": "", "post_date": "02/26/2019 17:36:21", "content": "Have a look at this discussion on an Earthquake Prediction Tutorial.
\n\nIt is important to watch the video, which is linked to on that post. But the discussion gives you an outline of the steps to follow.
", "votes": null, "replies": [] }, { "id": 480615, "author_name": "stanislavblinov", "author_url": "", "post_date": "02/28/2019 12:32:55", "content": "Try to see some public kernels for this competition:\nhttps://www.kaggle.com/c/LANL-Earthquake-Prediction/kernels\nThere's a lot of them explainig what's going on general
", "votes": null, "replies": [] }, { "id": 482934, "author_name": "cascio", "author_url": "", "post_date": "03/03/2019 21:57:08", "content": "Hello Abhishek,
\n\nI'm relatively new to Kaggle and ML too. I found the following to be most useful in getting started (not sure of your programming experience generally, but this is what I've reviewed so far):
\n\nKaggle Learn's Micro-Courses\n- Python Overview\n- Pandas Overview\n- Machine Learning Overview (Levels 1 & 2)
\n\nUser Inversion's \"Basic Feature Benchmark\" Kernel\n- Basic Solution to LANL Earthquake Prediction
\n\nI've also found reading certain discussion board posts and kernels to be useful, but don't get too bogged down if things appear complex or foreign. It will take time..
", "votes": null, "replies": [] } ], "raw_markdown_by_id": { "478537": "I am a newbie and have no idea how to deal with this stuff. Can someone suggest prerequisites for getting started with these contests? What should I learn to get started in minimum time? Suggest resources.", "478592": "To start with, go to kernel that has been created by others in 'knowledge' category. For example, 'Titanic' problem and see a kernel that has been created using a programming language that you are familiar with. Go through them line by line and try to understand what has been done. \n\nDon't give up and go through other kernels as well which are created by others. You will slowly will get to know how to get started with these contests. There is no minimum time set by anybody and it purely depends on your dedication to learn. Hope this helps!", "478839": "Have a look at this discussion on an [Earthquake Prediction Tutorial](https://www.kaggle.com/c/LANL-Earthquake-Prediction/discussion/81143). \n\nIt is important to watch the video, which is linked to on that post. But the discussion gives you an outline of the steps to follow.", "480615": "Try to see some public kernels for this competition:\nhttps://www.kaggle.com/c/LANL-Earthquake-Prediction/kernels\nThere's a lot of them explainig what's going on general", "482934": "Hello Abhishek,\n\nI'm relatively new to Kaggle and ML too. I found the following to be most useful in getting started (not sure of your programming experience generally, but this is what I've reviewed so far):\n\n***Kaggle Learn's Micro-Courses***\n- [Python Overview](https://www.kaggle.com/learn/python)\n- [Pandas Overview](https://www.kaggle.com/learn/pandas)\n- [Machine Learning Overview (Levels 1 & 2)](https://www.kaggle.com/learn/machine-learning)\n\n***User Inversion's \"Basic Feature Benchmark\" Kernel***\n- [Basic Solution to LANL Earthquake Prediction](https://www.kaggle.com/inversion/basic-feature-benchmark)\n\nI've also found reading certain discussion board posts and kernels to be useful, but don't get too bogged down if things appear complex or foreign. It will take time.." }, "source": "meta" }