![\"\"](\"https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1673888%2F5905bf26f78572103b14f00a4ca07277%2Fdrive.PNG?generation=1571816052467484&alt=media\")
\n![\"\"](\"https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1673888%2F71ebb2de19c57a13a4e175e3b1df6d99%2Fgiphy.gif?generation=1571816239438101&alt=media\")
\n
This competition remember me of the tutorial created by udacity: Udacity Self-Driving Car Engineer Nanodegree.
\n\nThis project was in fact inspired by the paper “End To End Learning For Self Driving Cars” by researchers at NVIDIA, who managed to get a car to drive autonomously by training a convolutional neural network to predict steering wheel angles based on steering angle data and images captured by three cameras (left, center, right) mounted in front of the car. The trained model is able to accurately steer the car using only the center camera. The diagram below shows the process used to create such an efficient model.\n![\"\"](\"https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1673888%2Fd9620a0779c842bb3b35f0dbaf4dfd28%2Fprocess.PNG?generation=1571816375889577&alt=media\")
You can find all code related to this project on github.\nThis is my video on youtube
", "messages": [ { "id": "655566", "postDate": "10/23/2019 07:40:17", "content": "\n
This competition remember me of the tutorial created by udacity: Udacity Self-Driving Car Engineer Nanodegree.
\n\nThis project was in fact inspired by the paper “End To End Learning For Self Driving Cars” by researchers at NVIDIA, who managed to get a car to drive autonomously by training a convolutional neural network to predict steering wheel angles based on steering angle data and images captured by three cameras (left, center, right) mounted in front of the car. The trained model is able to accurately steer the car using only the center camera. The diagram below shows the process used to create such an efficient model.\n
You can find all code related to this project on github.\nThis is my video on youtube
", "rawMarkdown": "\n\n\nThis competition remember me of the tutorial created by udacity: **[Udacity Self-Driving Car Engineer Nanodegree](https://www.udacity.com/course/self-driving-car-engineer-nanodegree--nd013)**.\n\nThis project was in fact inspired by the paper “[End To End Learning For Self Driving Cars](https://arxiv.org/abs/1604.07316)” by researchers at NVIDIA, who managed to get a car to drive autonomously by training a convolutional neural network to predict steering wheel angles based on steering angle data and images captured by three cameras (left, center, right) mounted in front of the car. The trained model is able to accurately steer the car using only the center camera. The diagram below shows the process used to create such an efficient model.\n\n\nYou can find all code related to this project on [github](https://github.com/HamdiTarek/Self_Driving_Car).\nThis is my [video](https://www.youtube.com/watch?v=L66UtaWeYHA&t=11s) on youtube", "votes": null }, { "id": "655632", "postDate": "10/23/2019 09:38:18", "content": "Very useful @hamditarek 👍. Thanks!
", "rawMarkdown": "Very useful @hamditarek 👍. Thanks!", "votes": null }, { "id": "655647", "postDate": "10/23/2019 10:20:38", "content": "You are welcome @phunghieu
", "rawMarkdown": "You are welcome @phunghieu", "votes": null }, { "id": "655850", "postDate": "10/23/2019 15:17:41", "content": "Thanks @hamditarek . Like Mr Bibek , you are everywhere in Kaggle too 😄 . Appreciate the hard work.
", "rawMarkdown": "Thanks @hamditarek . Like Mr Bibek , you are everywhere in Kaggle too 😄 . Appreciate the hard work.", "votes": null }, { "id": "655857", "postDate": "10/23/2019 15:28:23", "content": "Thanks @khairulislam, so kind of you
", "rawMarkdown": "Thanks @khairulislam, so kind of you", "votes": null }, { "id": "659068", "postDate": "10/27/2019 02:51:33", "content": "Thanks for sharing the information!
", "rawMarkdown": "Thanks for sharing the information!", "votes": null }, { "id": "659484", "postDate": "10/27/2019 18:59:34", "content": "You are welcome
", "rawMarkdown": "You are welcome", "votes": null }, { "id": "1379358", "postDate": "07/07/2021 09:49:57", "content": "Thanks for sharing. It is very useful! @hamditarek
\nI would also suggest trying Deep Evidential Regression .
Thanks for sharing. It is very useful! @hamditarek
\nI would also suggest trying Deep Evidential Regression .
Very useful @hamditarek 👍. Thanks!
", "votes": null, "replies": [ { "id": 655647, "author_name": "hamditarek", "author_url": "", "post_date": "10/23/2019 10:20:38", "content": "You are welcome @phunghieu
", "votes": null, "replies": [] } ] }, { "id": 655850, "author_name": "khairulislam", "author_url": "", "post_date": "10/23/2019 15:17:41", "content": "Thanks @hamditarek . Like Mr Bibek , you are everywhere in Kaggle too 😄 . Appreciate the hard work.
", "votes": null, "replies": [ { "id": 655857, "author_name": "hamditarek", "author_url": "", "post_date": "10/23/2019 15:28:23", "content": "Thanks @khairulislam, so kind of you
", "votes": null, "replies": [] } ] }, { "id": 659068, "author_name": "js9268", "author_url": "", "post_date": "10/27/2019 02:51:33", "content": "Thanks for sharing the information!
", "votes": null, "replies": [ { "id": 659484, "author_name": "hamditarek", "author_url": "", "post_date": "10/27/2019 18:59:34", "content": "You are welcome
", "votes": null, "replies": [] } ] } ], "raw_markdown_by_id": { "655566": "\n\n\nThis competition remember me of the tutorial created by udacity: **[Udacity Self-Driving Car Engineer Nanodegree](https://www.udacity.com/course/self-driving-car-engineer-nanodegree--nd013)**.\n\nThis project was in fact inspired by the paper “[End To End Learning For Self Driving Cars](https://arxiv.org/abs/1604.07316)” by researchers at NVIDIA, who managed to get a car to drive autonomously by training a convolutional neural network to predict steering wheel angles based on steering angle data and images captured by three cameras (left, center, right) mounted in front of the car. The trained model is able to accurately steer the car using only the center camera. The diagram below shows the process used to create such an efficient model.\n\n\nYou can find all code related to this project on [github](https://github.com/HamdiTarek/Self_Driving_Car).\nThis is my [video](https://www.youtube.com/watch?v=L66UtaWeYHA&t=11s) on youtube", "655632": "Very useful @hamditarek 👍. Thanks!", "655647": "You are welcome @phunghieu", "655850": "Thanks @hamditarek . Like Mr Bibek , you are everywhere in Kaggle too 😄 . Appreciate the hard work.", "655857": "Thanks @khairulislam, so kind of you", "659068": "Thanks for sharing the information!", "659484": "You are welcome", "1379358": "Thanks for sharing. It is very useful! @hamditarek \nI would also suggest trying [Deep Evidential Regression ](https://github.com/aamini/evidential-deep-learning)." }, "source": "meta" }