I'm doing a neural network prediction with my own datasets using Tensorflow. The first I did was a model that works with a small dataset in my computer. After this, I changed the code a little bit ...

I'm trying to run the Google Cloud ML engine locally for debugging purposes by running the command gcloud ml-engine local predict --model-dir=fasttext_cloud/ --json-instances=debug_instance.json. H...

I need to understand how to deploy models on Google Cloud ML. My first task is to deploy a very simple text classifier on the service. I do it in the following steps (could perhaps be shortened to ...

My Cloud ML training job completed with the output: "consumedMLUnits": 43.24 How do I use this information to determine the cost of the training job? I can't decide between the following...

My goal is to use training data (format: tfrecords) stored on Google Cloud storage when I run my Tensorflow Training App, locally. (Why locally? : I am testing before I turn it into a training pack...

I have a very simple trainer that follows the sample directory structure: /dist __init__.py setup.py /trainer __init__.py task.py Under the /dist directory, runs fine locally: $ gcloud ml-...

Google recently announced the Clould ML, https://cloud.google.com/ml/ and it's very useful. However, one limitation is that the input/out of a Tensorflow program should support gs://. If we use al...

I am trying to deploy a retrained version of the inception model on google cloud ml-engine. Gathering informations from the SavedModel documentation, this reference, and this post of rhaertel80, I ...

In the alpha release of CloudML's online prediction service, the format for exporting model was: inputs = {"x": x, "y_bytes": y} g.add_to_collection("inputs", json.dumps(inputs)) outputs = {"a": a...

Running the sample.sh script in Google Cloud Shell to call the below preprocess on set of images following the steps of flowers example. https://github.com/GoogleCloudPlatform/cloudml-samples/blo...

I tried to run tensorflow-wavenet on the google cloud ml-engine with gcloud ml-engine jobs submit training but the cloud job crashed when it was trying to read the json configuration file: with op...

The docs for setting up Google Cloud ML suggest installing Tensorflow version r0.11. I've observed that TensorFlow functions newly available in r0.12 raise exceptions when run on Cloud ML. Is there...

I have been working with google's machine learning platform, cloudML. Big picture: I'm trying to figure out the cleanest way to get their docker environment up and running on google compute instan...

I want to predict a jpeg image in cloud-ml. My training model is the inception model, and I would like to send the input to the first layer of the graph: 'DecodeJpeg/contents:0' (where I have to ...

I manage to retrain my specific classification model using the generic inception model following this tutorial. I would like now to deploy it on the google cloud machine learning following this ste...

I'm working on machine learning and I would like to use Google Cloud ml service. At this moment, I have trained my model with retrain.py code of Tensorflow (https://github.com/tensorflow/tensorflo...

I am trying to export my local tensorflow model to use it on Google Cloud ML and run predictions on it. I am following the tensorflow serving example with mnist data. There is quite a bit of diffe...

I want to use Google's Machine Learning thing with App Engine application written on python. This application should retrain TensorFlow models before every use, because of the investigation nature...

In Google Cloud ML (Machine Learning), I submitted a job, but it failed due to a Python error in the code. After fixing the error, how can I re-run the job? Should I submit a new job? When I'm d...

Online prediction is failing with "Unable to get elements from the feed as bytes". What does this mean and how can I fix it? I'm generating predictions using the following code: request_data = [{...

I am working on a multiclass classification problem consisting in classifying resumes. I used sklearn and its TfIdfVectorizer to get a big scipy sparse matrix that I feed in a Tensorflow model aft...

What is the suggest way of loading data from GCS? The sample code shows copying the data from GCS to the /tmp/ directory. If this is the suggest approach, how much data may be copied to /tmp/?