What are /r/tensorflow's favorite Products & Services?

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How is your math? If you're comfortable with multivariable calc, linear algebra, and some statistics (mostly the basics) then you should be ok. If not, it is helpful (but not totally necessary) to refresh.

This book that helped me out a ton when I was first learning TF, it has hands-on projects which cover SVMs, neural nets, computer vision, NLP, and RL. It doesn't shy away from the mathematical rigor, so you actually come away with a theoretical understanding of the algorithms, which makes a lot seem less like a black box, and because the projects are hands-on you actually know how to apply the theory into actual code.

Your data actually is technically labelled by virtue of being in labelled folders. There's a way using the tf.keras.utils.image_dataset_from_directory to import your images and the folder names as their labels and generate a tf.data.Dataset object. The tensorflow api docs have more info and it's used in a few tutorials across the site (all linked from this page)

I would start from wav to numpy arrays then to tensors >>> from scipy.io.wavfile import read >>> a = read("adios.wav") >>> numpy.array(a[1],dtype=float) array([ 128., 128., 128., ..., 128., 128., 128.])

typically it would be bytes which are then ints... here we just convert it to float type

you can read about read here http://www.scipy.org/doc/api_docs/SciPy.io.wavfile.html

I am preparing too .... I have done my research too you have everything other people are pointing too , except udacity course udacity

you may check it out

Hi Don, this is a very nice hello world! Congratz!

I had a lot of fun with your page. I like to test "hard to guess" pictures or try to see what gives it a hard time. I must say that this is a nice baseballbat!

Great work! What's the next step?

If you would, a report about it in English:

https://thenextweb.com/neural/2020/03/02/alibabas-new-ai-system-can-detect-coronavirus-in-seconds-with-96-accuracy/

I use an add-on chip that that comes with google's visual diy kit, and it handles the model inference. Unfortunately, it doesn't seem to be for sale anymore but found something similar on amazon, the Intel Movidius Neural Compute Stick. If for some unlikely reason that doesn't work, nvidia sells a jetson nano that can often replace a pi and handles inference even faster. GL!

Idk wdym by advanced, but this is an old thing I made (lol don't judge or ask why) a year-ish ago https://www.notion.so/sarvasvarora/Keras-Functional-API-b117580f170e49b6b902dd27bd55a927

Might be useful ¯\_(ツ)_/¯

Ya. I found this book to be very helpful when I first started. dataset preprocessing is actually a very in depth field with many different algorithms and processes to prep your data. I am surprised your search turned up small results. I also have an PDF copy of another book that I might be able to send if you want. It's much more in depth and covers data preprocessing and topics like that.

How about one of these...

https://aws.amazon.com/marketplace/pp/B01EYKBEQ0?ref=cns_srchrow

https://aws.amazon.com/marketplace/pp/B01M0AXXQB?ref=cns_srchrow

I know that the first one has all of the nVidia drivers (CUDA, CuDNN, etc) loaded because it says so on the description.

The second one doesn't explicitly say that it has all of the drivers loaded, but this is an official Amazon AMI so surely it will.

The second AMI is free (you don't pay extra for the software, you only pay for the instance you're using). The first one is not free, it adds about 10% to the cost of the instance after your free trial is over.

Udacity has a good course on deep learning with Tensorflow that can introduce you to how to work with the Tensorflow API. That and the Tensorflow documentation are a good place to start.

i am currently using this notion notebook to help me cover the exam essentials

https://www.notion.so/Getting-TensorFlow-Developer-Certified-Curriculum-66e97512073f4ca79a6eea4b644b1a5d

ps: i didn't create this i am just using it , i got it from this youtube video https://youtu.be/ya5NwvKafDk

I assume, since you're talking about captcha, that you're using an image input.

As for the error that you've pasted in your message, it seems like either the model isn't being loaded properly, or the image isn't being read (note the shape of the tensor the error mentions).

Have a look at this. http://flask.pocoo.org/docs/1.0/patterns/fileuploads/

I hope this helps.

I almost always use flask. It's quick and easy, but make sure you load the model only once during, and not every time the API is called. Doesn't get easier than that.

from flask import Flask

app = Flask(__name__)

@app.route("/classification_result")
def classify():
    do_something()

if __name__ == "__main__":
    load_model()
    app.run()

Have a look at this for more details:

http://flask.pocoo.org/

I use pytorch svd for hundreds of thousands multidimensional vector's and I've found it really easy to use. I have to note there's a bug right now in the partial matrix svd calculation, which is probably a strain for gpus and really big calculations. I recommend you try it, it's easy to pickup:

u, s, v = torch.svd(matrix)

edit: also sparse matrices (haven't used them): https://pytorch.org/docs/master/sparse.html

conda create —name bobsburgers tensorflow-gpu conda activate bobsburgers

You will need to download anaconda here.

Conda will do the hard work of versioning with NVIDIA’a software. It will only be in the given virtual environment though, so conda activate will be the prerequisite before running your code.

Note this will install tensorflow 2 by default. You can use pip to override and install a specific version or tensorflow afterward.

Tensorflow attention_ocr looks relatively new you can check at below link

https://github.com/tensorflow/models/tree/master/research/attention_ocr

Tesseract’s latest ocr is based on LSTM model you can try it. When I tried couple of months ago I got decent results..

https://github.com/tesseract-ocr/tesseract

I have an Asus Laptop with a gtx 1070 (NVIDIA GeForce GTX 1070 with Max-Q Design). The version of tensorflow I have installed is 2.4.1. So from what you've asked, it sounds like I just need to download an older version of tensorflow. Is that right?

Congrats on your book! Here's a link if anyone is interested. Don't see the option to 'look inside' but will check it out from the kindle sample.

https://www.amazon.co.uk/Hands-Machine-Learning-Scikit-Learn-TensorFlow/dp/1492032646

^ might focus too much on machine learning aspect but its all encompassing as far as tensorflow techniques go

Hi i actually made an android app (<12mb) with tensorflow cnn model to detect memes in phone and help clear them, it is amazing to see the results, i hope devlopers start taking full advantage of tensorflow image classification(cnn), this would have not been possible using openCV... at least accuracy wise. btw check my app out at: https://play.google.com/store/apps/details?id=com.slitwire.memecleaner