Hi everyone.
\nI don't know how to do it or what machine learning methods should I use for competitions like this. I guess this competition is image processing. Am i right?
\nAs a result, what would you recommend to someone who has never seen such a competition like this, and has no idea but wants to focus on this competition? Or what would you recommend?
A good start is probably familiarizing yourself with the public kernels and what has been already posted to the forums 🙂 There is a lot of good info there.
\nWhen looking at kernels, because of the limitation of the pipeline and how big the dataset is, people generally split their work into trianing and inference notebooks.
\nIf you are new to computer vision, this competition might be tough to get started with as there is a lot of complexity in dealing with the data and the models aren ot easy to train.
\nYou might rather want to get started with another, simpler competition, like for instance the Paddy competition and the series of notebooks by @jhoward here: First Steps: Road to the Top, Part 1.
", "rawMarkdown": "A good start is probably familiarizing yourself with the public kernels and what has been already posted to the forums 🙂 There is a lot of good info there.\n\nWhen looking at kernels, because of the limitation of the pipeline and how big the dataset is, people generally split their work into trianing and inference notebooks.\n\nIf you are new to computer vision, this competition might be tough to get started with as there is a lot of complexity in dealing with the data and the models aren ot easy to train. \n\nYou might rather want to get started with another, simpler competition, like for instance the Paddy competition and the series of notebooks by @jhoward here: [First Steps: Road to the Top, Part 1](https://www.kaggle.com/code/jhoward/first-steps-road-to-the-top-part-1). ", "votes": 3, "replies": [ { "id": 2061699, "postDate": "2022-12-11T12:18:04.257Z", "content": "Dear Radek, many thanks for your quick response . I have never worked on c.v. I will check and focus sequentially what you mentioned. !!
", "rawMarkdown": "Dear Radek, many thanks for your quick response . I have never worked on c.v. I will check and focus sequentially what you mentioned. !!\n", "votes": 1 } ] }, { "id": 2061231, "postDate": "2022-12-10T21:09:29.377Z", "content": "Hi everyone.
\nI don't know how to do it or what machine learning methods should I use for competitions like this. I guess this competition is image processing. Am i right?
\nAs a result, what would you recommend to someone who has never seen such a competition like this, and has no idea but wants to focus on this competition? Or what would you recommend?
A good start is probably familiarizing yourself with the public kernels and what has been already posted to the forums 🙂 There is a lot of good info there.
\nWhen looking at kernels, because of the limitation of the pipeline and how big the dataset is, people generally split their work into trianing and inference notebooks.
\nIf you are new to computer vision, this competition might be tough to get started with as there is a lot of complexity in dealing with the data and the models aren ot easy to train.
\nYou might rather want to get started with another, simpler competition, like for instance the Paddy competition and the series of notebooks by @jhoward here: First Steps: Road to the Top, Part 1.
", "votes": 3, "replies": [ { "id": 2061699, "author_name": "Çağatay Kılınç", "author_url": "", "post_date": "2022-12-11T12:18:04.257000", "content": "Dear Radek, many thanks for your quick response . I have never worked on c.v. I will check and focus sequentially what you mentioned. !!
", "votes": 1, "replies": [] } ] } ], "raw_markdown_by_id": { "2061285": "A good start is probably familiarizing yourself with the public kernels and what has been already posted to the forums 🙂 There is a lot of good info there.\n\nWhen looking at kernels, because of the limitation of the pipeline and how big the dataset is, people generally split their work into trianing and inference notebooks.\n\nIf you are new to computer vision, this competition might be tough to get started with as there is a lot of complexity in dealing with the data and the models aren ot easy to train. \n\nYou might rather want to get started with another, simpler competition, like for instance the Paddy competition and the series of notebooks by @jhoward here: [First Steps: Road to the Top, Part 1](https://www.kaggle.com/code/jhoward/first-steps-road-to-the-top-part-1). ", "2061231": "Hi everyone. \nI don't know how to do it or what machine learning methods should I use for competitions like this. I guess this competition is image processing. Am i right?\nAs a result, what would you recommend to someone who has never seen such a competition like this, and has no idea but wants to focus on this competition? Or what would you recommend?" } }