Finally !! A video from Siraj that actually explains something instead of those useless memes. This is how you should make rest of your videos. This was one of your best videos so far.
As others said, LOVE the "live" style video. Took you total of 30-40 mins to make without having to edit and add memes. And we take more in without getting distracted by the edits and memes.
Stopped at 4:30 right away. You have improved a lot. I love this new style where you toned down a bit and discuss and talk normally like a cool teacher. Really looking forward to what you will offer next with your talent and this new style. This channel is now perfect to learn machine learning from. Already recommended you to my entire classroom. Thank you very much, Siraj.
@Siraj I recently started following your channel, I am a student of Machine Learning and your videos have helped a lot, Thank you. Keep up the good work !
I've been working with ML in Unity for about a month now, and i gotta say, it's stupidly simple. really, all you do is add some components and write how an agent can move, start up mlagents-learn in an anaconda environment with tensorflow, and it'll start training. If you know a little c#, i definitely recommend this.
this comment is the equivalent of Kanye: "Yo, Taylor, I'm really happy for you, I'ma let you finish, but Beyoncé had one of the best videos of all time!" lol
Ah ah :) Awesome Video ! Some people (..haters..) might be upset at you, since you are sharing and explaining what could make some car company dominating the car autonomous market.
Just to add: The reason why x/127.5-1.0 is there to fan in to 1st layer is to just normalize the pixel inputs between -1 & +1. Gradient descent converges quickly if inputs are scaled and normalized to same range. for RGB color space pixel varies 0-255 & x/12.7.5-1 will normalize them to -1,+1. Interestingly they have preprocessed the image from RGB to YUV color space where pixels value ranges would be further reduced because Y = 0.299R + 0.587G + 0.114B U = 0.492 (B-Y) V = 0.877 (R-Y) which helps to converge better.
I have a few things to clarify. When I run the drive.py file with the model.h5 file, though it says 'Recording this run' and starting wsgi, nothing happens after that. 1. Do we need Unity Engine and load the Udacity Simulator on that? if yes, then does Unity work on Ubuntu 16.04 2. The python files, the .exe of the simulator and also the image folder which contains the data is in the same folder. The driving_log.csv has the absolute paths of the images. Where should each component be present? Is there some directory problem here the reason for my problem? 3. What are the arguments needed to be provided by us while running the drive.py and train.py file? will the drive.py file work even when the model is not saved as a .h5 and saved as .ckpt?
You are doing an awesome work. And you are very creative. :) I have few a questions siraj: 1)-Its seems so simple, Is this being used for real self driving car ? where is the catch ? 2)- If this is it then should all the companies stop working on semantic segmentation or object detection networks ? 3)- Do you think the network will learn which particular part of image lead to the output ?. (example : a stop sign lead to braking)
Just a question. Isn't end to end deep learning for a self driving car extremely unreliable? Like in realistic world we'll never be able to implement this because real world has so many variables and providng data that covers all of them satisfactorily is insane. Also we still can't be sure NN learnt everything correctly. Wouldn't approach where we do object and lane detection first then generate route be better?
i am not sure if u will read this comment .. nevertheless i wanted to say this.. The approach here is only to see a single frame and take decision. but it DO NOT consider any sequential data, like no time series data at all .. This will critically lose a lot of info to understand the traffic and there is no tract of state variables like ego vehicle velocity, target velocity.. This is just single image analysis without knowing the past at all .. is this any good for real world problem. ? I wish you can do a video only on Deep learning architectures for Autonomous driving.. there is a lot more than just seeing a frame and inferring a steering angle.. i guess you will agree..
[Q] How do you control such a car? I have trained in another game "self-driving car" with much smaller (naive) network and data just for curiosity if I'm able to output any values and it surprised me because it did actually learn to keep his lane (It did far more than I expected). But I have no control over him. I can't tell him to exit highway or go right on the next intersection. I had an idea to add to the images some data which will tell "go right" and train on that or connect another input layer after the CNN into Dense layers with data like "go straight/left/right" etc. but it didn't feel correct. For now I thought end-to-end for self-driving cars was rather toy experiment and not real use case but maybe it's not. Thank you.
How would we go on about implementing navigation/direction in it, for instance we want the car to drive between 2 points but we need to tell it when to make a turn
Sir i trained my self driving car and saved the csv file in the desktop but when i run the program in spyder it returns an error: FileNotFoundError: \\data\\driving_log.csv' does not exist. What did i do wrong? Please help me. Thank you.
This is an awesome video, thanks! GREAT presentation. Wondering if I can record my own video and input it. For instance, currently building an autonomous mower, this could be useful if I could record video of RC crawler over yard, and use that to train the autonomous mower.
Hey Siraj could you do a video illustrating how GAN's could be used to generate 3D models/pictures/videos using 3D Convolution networks. Thanks and keep it up!
Can't get it to run. Getting errorsTraceback (most recent call last): File "model.py", line 163, in main() File "model.py", line 159, in main train_model(model, args, *data) File "model.py", line 120, in train_model verbose=1) File "D:\Docs\Anaconda3\envs\car-behavioral-cloning\lib\site-packages\keras\models.py", line 924, in fit_generator pickle_safe=pickle_safe) File "D:\Docs\Anaconda3\envs\car-behavioral-cloning\lib\site-packages\keras\engine\training.py", line 1481, in fit_generator str(generator_output)) ValueError: output of generator should be a tuple (x, y, sample_weight) or (x, y). Found: None
It took me a while to get this to run, turns out, the csv file is not perfect, you have to add a header to the csv file that reads "center,left,right,steering,speed,throttle,brake".
I have a few things to clarify. When I run the drive.py file with the model.h5 file, though it says 'Recording this run' and starting wsgi, nothing happens after that. 1. Do we need Unity Engine and load the Udacity Simulator on that? if yes, then does Unity work on Ubuntu 16.04 2. The python files, the .exe of the simulator and also the image folder which contains the data is in the same folder. The driving_log.csv has the absolute paths of the images. Where should each component be present? Is there some directory problem here the reason for my problem? 3. What are the arguments needed to be provided by us while running the drive.py and train.py file? will the drive.py file work even when the model is not saved as a .h5 and saved as .ckpt? 4. How to add the headers to the csv file?
When i try to run the model.py file i have this error i am using python 3.5.4 IndexError: boolean index did not match indexed array along dimension 0; dimension is 160 but corresponding boolean dimension is 66
Hey Siraj. I am halfway through the Coursera (Andrew Ng) Machine Learning course and want to be able to do the cool stuff that you do. Where do I go next from there? I have a dream to be able to generate images, videos, sounds in the next 12 months. I am willing to dedicate hours per day to achieve this. I do realize you cover literally everything but I am not on that level yet and most things woosh over my head.
You are on the right track I finished that course 2 months ago and it took me 3 months to get through to really understand. I would recommend taking the Udacity course after. Machine Learning is really surprising and I am not on Siraj level but I hope to get better and better the more I do it. Just make some fun projects after going though each courses and challenge yourself.
New Name so Employers don't find me I'm neither an expert nor a video creator, but I created a Machine Learning Basics playlist on my account of other videos that helped me understand the high level principles. I think you can find it by looking on my "channel"?
New Name so Employers don't find me: Udacity Deep learning Foundation is your key to open all the locked doors. I'm currently enrolled in that course and just after few weeks, i already feel myself covering a lot of breadth that i would possibly not able to do somewhere else!
Could you shed some light on the image transformations happening before the images are fed into the CNN ( from the end to end learning paper from nvidia)?
@Siraj Raval I am downloading the Udacity simulator using below link , but where is the executable file in MAC system ?? I am not able to install in MAC Mac
If you're curious about making an autonomous driving project, I made a simulator that could help too. It is free and open source. The project is at: github.com/joshi1983/IARRCSim It hosts a site and HTTP-based API that you can test your autonomous driving code with. You could write your code in any language that supports making HTTP requests such as Python, Java... It simulates LIDAR, ultrasonic, and camera sensors. It also comes with a controllable drone on the simulated car that gives a bird's eye view of the car from its simulated downward-facing camera. IARRCSim has some similarities to what Udacity's simulator does but is more targeted for RC cars and supports a wider range of sensors. It was originally made for a university robotic car competition.
Siraj, could u make up a tutorial how to use your readme data, i.e. how to rebuilt the model? I tried quite hard but i wasn't successful.... Would be awesome, thanks.
how did you balance this data? if the outputs are all different sizes, wouldn't the data be more bias towards the highest output data? therefore the model would not generalise well on new data? interesting, great Vid
How can I run the Udacity simulator showing (or printing into a file) logs? Data sent by the "steer" socket event are not recognized by the simulator but I've no feedback on what's going wrong.
Hey Siraj, Can you please tell me how does a self-driving car choose the route when there is multiple paths available? For example a T-point or a road intersection?
Do you think enrolling in the Self-Driving Car Engineer Nano-degree Program is necessary to build a real self-driving car? If so, tell me more. If not, can you provide some additional concrete resources so that I can get started to build one of my own?
awesome video Siraj! I did a similar project making a self driving car using a racing video game. I followed Sentdex's series on it. I posted a video on my channel with results if you'e interested. One question: Have you tried using a model with LSTM? my driver will get stuck and push the brake key too often.
Great Video again. One Question about the CNN. Does the CNN actually still need to "classify" the pictures? Since it only needs to recognize certain shapes which are stacked (basically a pattern) to learn the right steering direction. Thanks
So here's a doubt. If I train the car in one track and try autonomous mode on another track(but keeping the surroundings same, the track itself would be different) , will it work?
Hi @Siraj What is utils? And how you imported? I have installed all the libraries but while importing it is showing utils not exist. Please, someone help!! Thank You in advance!!
Thanks Siraj for another great tutorial. Would you know if there's a way to change the max speed of the vehicle in the simulator? Also the gamepad doesn't seem to work for steering in the February release but it does in the November release. If anyone in the comments could help me out with this that would be great. Cheers
Hey Siraj since the version of keras got updated the INPUT_SHAPE is deprecated so what is the Input_shape means here? I need to know the extract value of it can u explain me in detail or a reference will be great help Thanks for the awesome video!
Can you make a simple arduino based neural network for just 4-6 neuron to optimize a sensor reading for machine learning. Lets say a distance sensor. Indepedent of processing only using arduino.
Love the slower pace, really lets me understand what's going on!
noted
Meantime me at 1.5x :D
I love the way you are so passionate about teaching people machine learning. More people need to see these videos. Thanks for doing what you're doing.
thx!
Finally !! A video from Siraj that actually explains something instead of those useless memes.
This is how you should make rest of your videos. This was one of your best videos so far.
thx love u
As others said, LOVE the "live" style video. Took you total of 30-40 mins to make without having to edit and add memes. And we take more in without getting distracted by the edits and memes.
great feedback thx
Stopped at 4:30 right away. You have improved a lot. I love this new style where you toned down a bit and discuss and talk normally like a cool teacher. Really looking forward to what you will offer next with your talent and this new style. This channel is now perfect to learn machine learning from. Already recommended you to my entire classroom. Thank you very much, Siraj.
@Siraj I recently started following your channel, I am a student of Machine Learning and your videos have helped a lot, Thank you. Keep up the good work !
I've been working with ML in Unity for about a month now, and i gotta say, it's stupidly simple. really, all you do is add some components and write how an agent can move, start up mlagents-learn in an anaconda environment with tensorflow, and it'll start training. If you know a little c#, i definitely recommend this.
This is the best explained video you have ever created. Continue to make videos like this,slow paced but well explained! :)
will do thx
Your AI videos are a gift, Siraj. Thanks so much for making these cool, entertaining tutorials
"it's a chain of whatever" - RAVAL, Siraj
love the "live" style video
thx noted
You did a good job but I would vote for @sentdex on his effort of creating self-driving car with GTA V series.
Mahmoud Hisham he didn't succeed siraj always succeeds
this comment is the equivalent of Kanye: "Yo, Taylor, I'm really happy for you, I'ma let you finish, but Beyoncé had one of the best videos of all time!" lol
Mahmoud Hisham watcht him on twitch, Charles is training 24/7
chill folks, this isn't a competition! :P
ok thx
Love this style of video! If you could make your videos more like this, that'd be awesome!
noted thx
Ah ah :) Awesome Video ! Some people (..haters..) might be upset at you, since you are sharing and explaining what could make some car company dominating the car autonomous market.
huh, I found a hidden gem, you've been working, from your channel, I can see you have worked alot on AI before AI became a common thing to use
Just to add:
The reason why x/127.5-1.0 is there to fan in to 1st layer is to just normalize the pixel inputs between -1 & +1. Gradient descent converges quickly if inputs are scaled and normalized to same range. for RGB color space pixel varies 0-255 & x/12.7.5-1 will normalize them to -1,+1. Interestingly they have preprocessed the image from RGB to YUV color space where pixels value ranges would be further reduced because
Y = 0.299R + 0.587G + 0.114B
U = 0.492 (B-Y)
V = 0.877 (R-Y)
which helps to converge better.
I have a few things to clarify. When I run the drive.py file with the model.h5 file, though it says 'Recording this run' and starting wsgi, nothing happens after that.
1. Do we need Unity Engine and load the Udacity Simulator on that?
if yes, then does Unity work on Ubuntu 16.04
2. The python files, the .exe of the simulator and also the image folder which contains the data is in the same folder. The driving_log.csv has the absolute paths of the images. Where should each component be present? Is there some directory problem here the reason for my problem?
3. What are the arguments needed to be provided by us while running the drive.py and train.py file?
will the drive.py file work even when the model is not saved as a .h5 and saved as .ckpt?
My drive.py didn't connect to the simulator, how do i fix this ?
Hello . Can you please help . The python client says connection accepted but in the autonomous mode the car is not running. Please help.
awesome video as usual and thanks for making this knowledge available to the masses
Siraj! If you could increase the audio quality that would be awesome news for our ears.
i will from now on promise
Why did't you run the test code show us the car driving in autonomous mode?
because training the model took him about 8 hours
sentdex did this in GTA last month.
i love when charles do evasive manuvers.
charles is training twitch . tv/ sentdex
after this training , jugdment day by skynet!
Weird, I had no idea I failed
sentdex can you make some transfer learning to this model?
Upgrading the audio of the vidio will be definitely an amazing improvement.
bro you are an another level.Thanks for sharing this
You are doing an awesome work. And you are very creative. :)
I have few a questions siraj:
1)-Its seems so simple, Is this being used for real self driving car ? where is the catch ?
2)- If this is it then should all the companies stop working on semantic segmentation or object detection networks ?
3)- Do you think the network will learn which particular part of image lead to the output ?. (example : a stop sign lead to braking)
You are actually self-driving car engineer and all that after this course?
Just a question. Isn't end to end deep learning for a self driving car extremely unreliable? Like in realistic world we'll never be able to implement this because real world has so many variables and providng data that covers all of them satisfactorily is insane. Also we still can't be sure NN learnt everything correctly.
Wouldn't approach where we do object and lane detection first then generate route be better?
Oh cool! I didn't expect a video today!
thank you for self driving car simulator video, do you have any interest in talking about numenta htm or ibm watson in future video?
Hello Siraj, is there any possibility of you making a tutorial on Semantic segmentation using Tensor flow?
thank you for your videos from Latvia)
keep it up and thanks for making me understand and interested in ML
Bro i want to learn machine learning and self driving car projects
very cool video. Thanks for the upload!
Thank you Siraj for this amazing video
Thanks for the awesome tutorial.
i am not sure if u will read this comment .. nevertheless i wanted to say this.. The approach here is only to see a single frame and take decision. but it DO NOT consider any sequential data, like no time series data at all .. This will critically lose a lot of info to understand the traffic and there is no tract of state variables like ego vehicle velocity, target velocity.. This is just single image analysis without knowing the past at all .. is this any good for real world problem. ? I wish you can do a video only on Deep learning architectures for Autonomous driving.. there is a lot more than just seeing a frame and inferring a steering angle.. i guess you will agree..
good enough for a start i say !
This is so cool. Thanks for the video. Just curious how long did it take you to finish this project.
[Q] How do you control such a car? I have trained in another game "self-driving car" with much smaller (naive) network and data just for curiosity if I'm able to output any values and it surprised me because it did actually learn to keep his lane (It did far more than I expected). But I have no control over him. I can't tell him to exit highway or go right on the next intersection. I had an idea to add to the images some data which will tell "go right" and train on that or connect another input layer after the CNN into Dense layers with data like "go straight/left/right" etc. but it didn't feel correct. For now I thought end-to-end for self-driving cars was rather toy experiment and not real use case but maybe it's not. Thank you.
ValueError: output of generator should be a tuple (x, y, sample_weight) or (x, y). Found: None
how to solve it?
github.com/llSourcell/How_to_simulate_a_self_driving_car/issues/7
last answer...
How did you install its dependencies please help me out. Thank you
How would we go on about implementing navigation/direction in it, for instance we want the car to drive between 2 points but we need to tell it when to make a turn
Good video, but it will be great if you explain 'why' instead of 'what' a line of code does.
Thanks Siraj!
Sir i trained my self driving car and saved the csv file in the desktop but when i run the program in spyder it returns an error: FileNotFoundError: \\data\\driving_log.csv' does not exist. What did i do wrong? Please help me. Thank you.
This is an awesome video, thanks! GREAT presentation. Wondering if I can record my own video and input it. For instance, currently building an autonomous mower, this could be useful if I could record video of RC crawler over yard, and use that to train the autonomous mower.
when i execute the code, i get the following error....
sio = socketio.Server()
AttributeError: 'module' object has no attribute 'Server'
Hey Siraj could you do a video illustrating how GAN's could be used to generate 3D models/pictures/videos using 3D Convolution networks. Thanks and keep it up!
sorry if i missed, why 3 video inputs?
Can't get it to run. Getting errorsTraceback (most recent call last):
File "model.py", line 163, in
main()
File "model.py", line 159, in main
train_model(model, args, *data)
File "model.py", line 120, in train_model
verbose=1)
File "D:\Docs\Anaconda3\envs\car-behavioral-cloning\lib\site-packages\keras\models.py", line 924, in fit_generator
pickle_safe=pickle_safe)
File "D:\Docs\Anaconda3\envs\car-behavioral-cloning\lib\site-packages\keras\engine\training.py", line 1481, in fit_generator
str(generator_output))
ValueError: output of generator should be a tuple (x, y, sample_weight) or (x, y). Found: None
Same problem here!
Same problem here, any resolution yet?
go to utils change the picture size to 160, 320
Could you show and make a simple ai for a game using openAi and a custom environment?
sentdex inspires siraj
I love them both
indeed love u
It took me a while to get this to run, turns out, the csv file is not perfect, you have to add a header to the csv file that reads "center,left,right,steering,speed,throttle,brake".
It was 'center,left,right,steering,throttle,brake,speed' for me.
Jaffin MK I never got this working so maybe that will help, I got it to compile but it wouldn't train
Why? Whats the problem?
I have a few things to clarify. When I run the drive.py file with the model.h5 file, though it says 'Recording this run' and starting wsgi, nothing happens after that.
1. Do we need Unity Engine and load the Udacity Simulator on that?
if yes, then does Unity work on Ubuntu 16.04
2. The python files, the .exe of the simulator and also the image folder which contains the data is in the same folder. The driving_log.csv has the absolute paths of the images. Where should each component be present? Is there some directory problem here the reason for my problem?
3. What are the arguments needed to be provided by us while running the drive.py and train.py file?
will the drive.py file work even when the model is not saved as a .h5 and saved as .ckpt?
4. How to add the headers to the csv file?
When i try to run the model.py file i have this error i am using python 3.5.4
IndexError: boolean index did not match indexed array along dimension 0; dimension is 160 but corresponding boolean dimension is 66
github.com/llSourcell/How_to_simulate_a_self_driving_car/issues/16 they fixed!
Hey Siraj. I am halfway through the Coursera (Andrew Ng) Machine Learning course and want to be able to do the cool stuff that you do. Where do I go next from there? I have a dream to be able to generate images, videos, sounds in the next 12 months. I am willing to dedicate hours per day to achieve this. I do realize you cover literally everything but I am not on that level yet and most things woosh over my head.
You are on the right track I finished that course 2 months ago and it took me 3 months to get through to really understand. I would recommend taking the Udacity course after. Machine Learning is really surprising and I am not on Siraj level but I hope to get better and better the more I do it. Just make some fun projects after going though each courses and challenge yourself.
yea I am working through the intro to machine learning course on Udacity... but I always find myself coming back to Siraj lol
New Name so Employers don't find me I'm neither an expert nor a video creator, but I created a Machine Learning Basics playlist on my account of other videos that helped me understand the high level principles. I think you can find it by looking on my "channel"?
New Name so Employers don't find me:
Udacity Deep learning Foundation is your key to open all the locked doors. I'm currently enrolled in that course and just after few weeks, i already feel myself covering a lot of breadth that i would possibly not able to do somewhere else!
I am on the same track too! I have finished upto week 2.
34:39 We are listening you carefully, Siraj
good
Tesla developer: guys note it down its free
Siraj, please cite the resources you use.
images.nvidia.com/content/tegra/automotive/images/2016/solutions/pdf/end-to-end-dl-using-px.pdf
Thanx for the pdf file
This is exactly what I'm looking for, thx!
You're awesome @Siraj.
Can you explain the back propagation in the convolution layer in terms of updating the kernels involved in another video perhaps ?
BTW great work !
can anybody help me with this steerin_angle=float(data["steering_angle"]) Value error :could not convert string to float : '0,00000'
print out data["steering_angle"], double check what you get
output of generator should be a tuple (x, y, sample_weight) or (x, y). Found: None
plz somebody help me !!!
Could you shed some light on the image transformations happening before the images are fed into the CNN ( from the end to end learning paper from nvidia)?
how to install udacity self driving car on macbook. I downloaded the file for mac but its not allowing me to run it..anyone tried on mac? please help
it seems to need a bunch of knowledge on those libraries and also basic idea of how neuro network works
@Siraj Raval I am downloading the Udacity simulator using below link , but where is the executable file in MAC system ?? I am not able to install in MAC
Mac
You fine sir...deserve more subscribers.
thx getting there
I did this whole project nothing ran as I wanted it to I setup the whole environment properly but nothing works help me please
If you're curious about making an autonomous driving project, I made a simulator that could help too. It is free and open source. The project is at: github.com/joshi1983/IARRCSim It hosts a site and HTTP-based API that you can test your autonomous driving code with. You could write your code in any language that supports making HTTP requests such as Python, Java... It simulates LIDAR, ultrasonic, and camera sensors. It also comes with a controllable drone on the simulated car that gives a bird's eye view of the car from its simulated downward-facing camera. IARRCSim has some similarities to what Udacity's simulator does but is more targeted for RC cars and supports a wider range of sensors. It was originally made for a university robotic car competition.
Superb Siraj
Siraj, do you know that you're awesome!?
Keep up the good work.
Nice one! Can u take up a session on Distributed Tensorflow????
How to create model.h5 file? if I run the model.py , it will be generated by system? Please giving me a information
Siraj, could u make up a tutorial how to use your readme data, i.e. how to rebuilt the model? I tried quite hard but i wasn't successful....
Would be awesome, thanks.
Could someone help me? I get the following error when I try to train the model: TypeError: ('Keyword argument not understood:', 'subsample')
sentdex, openai Robo Simulator, siraj udacity Simulator, but where is my convnet to Mars? i want to get to the Endboss elon 🤐
lets make one
how did you balance this data? if the outputs are all different sizes, wouldn't the data be more bias towards the highest output data? therefore the model would not generalise well on new data? interesting, great Vid
Do you have video on image segmentation
10:15
"It's just a chain of whatever" xD
How can I run the Udacity simulator showing (or printing into a file) logs? Data sent by the "steer" socket event are not recognized by the simulator but I've no feedback on what's going wrong.
This tutorial is really good!
hey sirraj could you guide on how to train this model on my own cutom dataset?
Did you find any solution to this? If yes, then please let me know.
Great video and fantastic content! thx
Hey Siraj, Can you please tell me how does a self-driving car choose the route when there is multiple paths available? For example a T-point or a road intersection?
Do you think enrolling in the Self-Driving Car Engineer Nano-degree Program is necessary to build a real self-driving car? If so, tell me more. If not, can you provide some additional concrete resources so that I can get started to build one of my own?
awesome video Siraj! I did a similar project making a self driving car using a racing video game. I followed Sentdex's series on it. I posted a video on my channel with results if you'e interested.
One question: Have you tried using a model with LSTM? my driver will get stuck and push the brake key too often.
Great Video again. One Question about the CNN. Does the CNN actually still need to "classify" the pictures? Since it only needs to recognize certain shapes which are stacked (basically a pattern) to learn the right steering direction. Thanks
So here's a doubt. If I train the car in one track and try autonomous mode on another track(but keeping the surroundings same, the track itself would be different) , will it work?
can anybody help me how can i made this project runable on my system
Siraj for the president gj
Great video! How do you integrate other cars, stop lights...?
Hi @Siraj What is utils? And how you imported? I have installed all the libraries but while importing it is showing utils not exist. Please, someone help!! Thank You in advance!!
Can you make a video on building automation testing environment for autonomous driving ,all using python...??? Or give a talk about it pls
Thanks Siraj for another great tutorial. Would you know if there's a way to change the max speed of the vehicle in the simulator? Also the gamepad doesn't seem to work for steering in the February release but it does in the November release. If anyone in the comments could help me out with this that would be great.
Cheers
Hey Siraj since the version of keras got updated the INPUT_SHAPE is deprecated so what is the Input_shape means here?
I need to know the extract value of it can u explain me in detail or a reference will be great help Thanks for the awesome video!
what does model.summary() do?
you are just outstanding
just loved it
Siraj, can I ask how computer games bot is made. It seems they are not using screen shot images, how they connect to the game information? Thanks!
Can you make a simple arduino based neural network for just 4-6 neuron to optimize a sensor reading for machine learning. Lets say a distance sensor. Indepedent of processing only using arduino.
Can I use this to train a reinforcement learning agent?
Please upgrade microphone and video camera. Apart from that video looks good.
absolutely i just did