I keep getting the following error whenever I try to create a new project in https://www.customvision.ai/projects for the labs 2 and 3.

I tried both S0 and F0 plans for the custom vision, But I still get the same error.

{
    "error": {
        "code": "TooManyRequests",
        "message": "The request is being throttled as the limit has been reached for operation type - Write_ObservationWindow_01:00:00. For more information, see - https://aka.ms/srpthrottlinglimits"
    }
}

The learning path - Explore computer vision in Microsoft Azure (Module 1) has some helpful information missing that I noticed is present in the subsequent Modules in the same learning path.

Module 1 is below

A subsequent Module is below

When we try to create a QnA service using the settings provided, when I go to the final review and create page, and click create, it turns up with an "undefined" error. This error was occurring both through the VM and when I tried to do the same outside the VM.

Hello @sherzyang and contributors,

There is another small typo on the file mslearn-ai900 / instructions / 00-run-batch.md.

The third, and last, step of the instructions is calling the MSLEARN-AI900 project folder as a file, it says: "This file contains the labs for the course."

While it should say "This folder contains the labs for the course."

As I am translating this repo to Portuguese to help Brazilian students, I am going through each word and finding a couple of typos. If I am being too picky, please let me know and I will stop opening these small issues. I can also fork this repo and suggest a pull request fixing this stuff if I may.

I am sorry if I am misusing it here, I am king of new to GitHub and I am still learning. Please let me know how I should behave when I find this small issues with the repo.

Once again, thank you very much for holding this repo and material. I is simply amazing and helped me a lot towards my AI-900 certification.

In the lab notebook called "08 - Speech.ipynb", when executing the code cell below the Speech synthesis title, the synthesized audio is not played.

Inspecting the result variable returned in the line result = speech_synthesizer.speak_text(response_text) reveals the following error details: "Connection was closed by the remote host. Error code: 1007. Error details: Starting September 1st, 2021 standard voices will no longer be supported for new users.".

This can be solved by manually specifying a neural voice just below the initialization of the speech_config variable:

speech_config.speech_synthesis_voice_name = 'en-US-ChristopherNeural'

Maybe there's a better option to fix it, but that worked for me.

There is just a small typo on the file mslearn-ai900/instructions/00 - Local development.md.

When referencing to the VS Code's download page, there is an extra ] on the Markdown syntax for the hyperlink. Having [download it here]](https://code.visualstudio.com/Download) instead of download it here .

I know it is not a big issue. But I hope to be helpful with these small observations.

Once again, thank you very much for this repo. It is an amazing source for studying and I am translating it to Portuguese to support the Brazilian community.

When working on the Create a language model with Language Understanding module's Exercise - Create a Language Understanding Application, I received a The term '-like' is not recognized as a name of a cmdlet, function, script file, or executable program. Check the spelling of the name, or if a path was included, verify that the path is correct and try again error (shown in the attached screenshot) for Line 20: if($predictedDevice -like ("*light*") -or (-like ("*fan*"))){. I have not modified anything outside of what the exercise calls for (the $appId, $key, and $endpointUrl variables).

In these 2 scenarios, when we try to consume the model in the Python notebook, even if details are correct about endpoint, project and key, you'll receive an "Access denied".

gaierror Traceback (most recent call last)
/anaconda/envs/azureml_py36/lib/python3.6/site-packages/urllib3/connection.py in _new_conn(self)
159 conn = connection.create_connection(
--> 160 (self._dns_host, self.port), self.timeout, **extra_kw
161 )

/anaconda/envs/azureml_py36/lib/python3.6/site-packages/urllib3/util/connection.py in create_connection(address, timeout, source_address, socket_options)
60
---> 61 for res in socket.getaddrinfo(host, port, family, socket.SOCK_STREAM):
62 af, socktype, proto, canonname, sa = res

/anaconda/envs/azureml_py36/lib/python3.6/socket.py in getaddrinfo(host, port, family, type, proto, flags)
744 addrlist = []
--> 745 for res in _socket.getaddrinfo(host, port, family, type, proto, flags):
746 af, socktype, proto, canonname, sa = res

gaierror: [Errno -3] Temporary failure in name resolution

During handling of the above exception, another exception occurred:

NewConnectionError Traceback (most recent call last)
/anaconda/envs/azureml_py36/lib/python3.6/site-packages/urllib3/connectionpool.py in urlopen(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, **response_kw)
676 headers=headers,
--> 677 chunked=chunked,
678 )

/anaconda/envs/azureml_py36/lib/python3.6/site-packages/urllib3/connectionpool.py in _make_request(self, conn, method, url, timeout, chunked, **httplib_request_kw)
380 try:
--> 381 self._validate_conn(conn)
382 except (SocketTimeout, BaseSSLError) as e:

/anaconda/envs/azureml_py36/lib/python3.6/site-packages/urllib3/connectionpool.py in _validate_conn(self, conn)
977 if not getattr(conn, "sock", None): # AppEngine might not have .sock
--> 978 conn.connect()
979

/anaconda/envs/azureml_py36/lib/python3.6/site-packages/urllib3/connection.py in connect(self)
308 # Add certificate verification
--> 309 conn = self._new_conn()
310 hostname = self.host

/anaconda/envs/azureml_py36/lib/python3.6/site-packages/urllib3/connection.py in _new_conn(self)
171 raise NewConnectionError(
--> 172 self, "Failed to establish a new connection: %s" % e
173 )

NewConnectionError: <urllib3.connection.HTTPSConnection object at 0x7f1930717e80>: Failed to establish a new connection: [Errno -3] Temporary failure in name resolution

During handling of the above exception, another exception occurred:

MaxRetryError Traceback (most recent call last)
/anaconda/envs/azureml_py36/lib/python3.6/site-packages/requests/adapters.py in send(self, request, stream, timeout, verify, cert, proxies)
448 retries=self.max_retries,
--> 449 timeout=timeout
450 )

/anaconda/envs/azureml_py36/lib/python3.6/site-packages/urllib3/connectionpool.py in urlopen(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, **response_kw)
766 body_pos=body_pos,
--> 767 **response_kw
768 )

/anaconda/envs/azureml_py36/lib/python3.6/site-packages/urllib3/connectionpool.py in urlopen(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, **response_kw)
766 body_pos=body_pos,
--> 767 **response_kw
768 )

/anaconda/envs/azureml_py36/lib/python3.6/site-packages/urllib3/connectionpool.py in urlopen(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, **response_kw)
766 body_pos=body_pos,
--> 767 **response_kw
768 )

/anaconda/envs/azureml_py36/lib/python3.6/site-packages/urllib3/connectionpool.py in urlopen(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, **response_kw)
726 retries = retries.increment(
--> 727 method, url, error=e, _pool=self, _stacktrace=sys.exc_info()[2]
728 )

/anaconda/envs/azureml_py36/lib/python3.6/site-packages/urllib3/util/retry.py in increment(self, method, url, response, error, _pool, _stacktrace)
445 if new_retry.is_exhausted():
--> 446 raise MaxRetryError(_pool, url, error or ResponseError(cause))
447

MaxRetryError: HTTPSConnectionPool(host='shush-fruits.cognitiveservices.azure.com', port=443): Max retries exceeded with url: /customvision/v3.1/prediction/b3c22f2d-12a4-4c90-a7aa-60cb1e9628e3/classify/iterations/fruits/image (Caused by NewConnectionError('<urllib3.connection.HTTPSConnection object at 0x7f1930717e80>: Failed to establish a new connection: [Errno -3] Temporary failure in name resolution',))

During handling of the above exception, another exception occurred:

ConnectionError Traceback (most recent call last)
/anaconda/envs/azureml_py36/lib/python3.6/site-packages/msrest/universal_http/requests.py in send(self, request, **kwargs)
141 request.url,
--> 142 **kwargs)
143 except requests.RequestException as err:

/anaconda/envs/azureml_py36/lib/python3.6/site-packages/requests/sessions.py in request(self, method, url, params, data, headers, cookies, files, auth, timeout, allow_redirects, proxies, hooks, stream, verify, cert, json)
541 send_kwargs.update(settings)
--> 542 resp = self.send(prep, **send_kwargs)
543

/anaconda/envs/azureml_py36/lib/python3.6/site-packages/requests/sessions.py in send(self, request, **kwargs)
654 # Send the request
--> 655 r = adapter.send(request, **kwargs)
656

/anaconda/envs/azureml_py36/lib/python3.6/site-packages/requests/adapters.py in send(self, request, stream, timeout, verify, cert, proxies)
515
--> 516 raise ConnectionError(e, request=request)
517

ConnectionError: HTTPSConnectionPool(host='shush-fruits.cognitiveservices.azure.com', port=443): Max retries exceeded with url: /customvision/v3.1/prediction/b3c22f2d-12a4-4c90-a7aa-60cb1e9628e3/classify/iterations/fruits/image (Caused by NewConnectionError('<urllib3.connection.HTTPSConnection object at 0x7f1930717e80>: Failed to establish a new connection: [Errno -3] Temporary failure in name resolution',))

During handling of the above exception, another exception occurred:

ClientRequestError Traceback (most recent call last)
in
4 # Open the image, and use the custom vision model to classify it
5 image_contents = open(os.path.join(test_folder, test_images[i]), "rb")
----> 6 classification = custom_vision_client.classify_image(project_id, model_name, image_contents.read())
7 # The results include a prediction for each tag, in descending order of probability - get the first one
8 prediction = classification.predictions[0].tag_name

/anaconda/envs/azureml_py36/lib/python3.6/site-packages/azure/cognitiveservices/vision/customvision/prediction/operations/_custom_vision_prediction_client_operations.py in classify_image(self, project_id, published_name, image_data, application, custom_headers, raw, **operation_config)
71 # Construct and send request
72 request = self._client.post(url, query_parameters, header_parameters, form_content=form_data_content)
---> 73 response = self._client.send(request, stream=False, **operation_config)
74
75 if response.status_code not in [200]:

/anaconda/envs/azureml_py36/lib/python3.6/site-packages/msrest/service_client.py in send(self, request, headers, content, **kwargs)
334 kwargs.setdefault('stream', True)
335 try:
--> 336 pipeline_response = self.config.pipeline.run(request, **kwargs)
337 # There is too much thing that expects this method to return a "requests.Response"
338 # to break it in a compatible release.

/anaconda/envs/azureml_py36/lib/python3.6/site-packages/msrest/pipeline/init.py in run(self, request, **kwargs)
195 pipeline_request = Request(request, context) # type: Request[HTTPRequestType]
196 first_node = self._impl_policies[0] if self._impl_policies else self._sender
--> 197 return first_node.send(pipeline_request, **kwargs) # type: ignore
198
199 class HTTPSender(AbstractContextManager, ABC, Generic[HTTPRequestType, HTTPResponseType]):

/anaconda/envs/azureml_py36/lib/python3.6/site-packages/msrest/pipeline/init.py in send(self, request, **kwargs)
148 self._policy.on_request(request, **kwargs)
149 try:
--> 150 response = self.next.send(request, **kwargs)
151 except Exception:
152 if not self._policy.on_exception(request, **kwargs):

/anaconda/envs/azureml_py36/lib/python3.6/site-packages/msrest/pipeline/requests.py in send(self, request, **kwargs)
70 try:
71 try:
---> 72 return self.next.send(request, **kwargs)
73 except (oauth2.rfc6749.errors.InvalidGrantError,
74 oauth2.rfc6749.errors.TokenExpiredError) as err:

/anaconda/envs/azureml_py36/lib/python3.6/site-packages/msrest/pipeline/requests.py in send(self, request, **kwargs)
135
136 try:
--> 137 return self.next.send(request, **kwargs)
138 finally:
139 if old_max_redirects:

/anaconda/envs/azureml_py36/lib/python3.6/site-packages/msrest/pipeline/init.py in send(self, request, **kwargs)
148 self._policy.on_request(request, **kwargs)
149 try:
--> 150 response = self.next.send(request, **kwargs)
151 except Exception:
152 if not self._policy.on_exception(request, **kwargs):

/anaconda/envs/azureml_py36/lib/python3.6/site-packages/msrest/pipeline/requests.py in send(self, request, **kwargs)
191 return Response(
192 request,
--> 193 self.driver.send(request.http_request, **kwargs)
194 )

/anaconda/envs/azureml_py36/lib/python3.6/site-packages/msrest/universal_http/requests.py in send(self, request, **kwargs)
331 """
332 requests_kwargs = self._configure_send(request, **kwargs)
--> 333 return super(RequestsHTTPSender, self).send(request, **requests_kwargs)
334
335

/anaconda/envs/azureml_py36/lib/python3.6/site-packages/msrest/universal_http/requests.py in send(self, request, **kwargs)
143 except requests.RequestException as err:
144 msg = "Error occurred in request."
--> 145 raise_with_traceback(ClientRequestError, msg, err)
146
147 return RequestsClientResponse(request, response)

/anaconda/envs/azureml_py36/lib/python3.6/site-packages/msrest/exceptions.py in raise_with_traceback(exception, message, *args, **kwargs)
49 error = exception(exc_msg, *args, **kwargs)
50 try:
---> 51 raise error.with_traceback(exc_traceback)
52 except AttributeError:
53 error.traceback = exc_traceback

/anaconda/envs/azureml_py36/lib/python3.6/site-packages/msrest/universal_http/requests.py in send(self, request, **kwargs)
140 request.method,
141 request.url,
--> 142 **kwargs)
143 except requests.RequestException as err:
144 msg = "Error occurred in request."

/anaconda/envs/azureml_py36/lib/python3.6/site-packages/requests/sessions.py in request(self, method, url, params, data, headers, cookies, files, auth, timeout, allow_redirects, proxies, hooks, stream, verify, cert, json)
540 }
541 send_kwargs.update(settings)
--> 542 resp = self.send(prep, **send_kwargs)
543
544 return resp

/anaconda/envs/azureml_py36/lib/python3.6/site-packages/requests/sessions.py in send(self, request, **kwargs)
653
654 # Send the request
--> 655 r = adapter.send(request, **kwargs)
656
657 # Total elapsed time of the request (approximately)

/anaconda/envs/azureml_py36/lib/python3.6/site-packages/requests/adapters.py in send(self, request, stream, timeout, verify, cert, proxies)
514 raise SSLError(e, request=request)
515
--> 516 raise ConnectionError(e, request=request)
517
518 except ClosedPoolError as e:

ClientRequestError: Error occurred in request., ConnectionError: HTTPSConnectionPool(host='shush-fruits.cognitiveservices.azure.com', port=443): Max retries exceeded with url: /customvision/v3.1/prediction/b3c22f2d-12a4-4c90-a7aa-60cb1e9628e3/classify/iterations/fruits/image (Caused by NewConnectionError('<urllib3.connection.HTTPSConnection object at 0x7f1930717e80>: Failed to establish a new connection: [Errno -3] Temporary failure in name resolution',))

On day 3 of the AI-900 study group we got to see the Azure Health Bot Project (www.microsoft.com/en-us/research/project/health-bot) as a sample for a bot created with Azure bot services.
The technical aspects are quite easy to comprehend, but I think the medical implications of this bot have not been captured adequately.
The AI learning course makes it very clear that we all should strive for development of "responsible AI" and that a bot should be able to hand over to a human seamlessly.
The health bot can be given all sorts of medical conditions, from simple, low-level symptoms all the way up to life-threatening emergencies.
In the demo, the bot was given emergency symptoms that can indicate a stroke, yet the bot continued to ask for things like temperature or if there are streaks in the throat, wasting valuable time (or, in a real world situation, having the patient quit the conversation without getting help).
Even though it is "just" a demo, such real-world implications arise quickly, so I think the bot should behave reasonable responsible by handing over to a human in case of emergency earlier.

I faced problem in Module 10- Language Understanding in the last step 'Add Voice Control' when using Visual Studio Code to execute the command. It has the error that ModuleNotFoundError: No module named 'azure' . It probably due to the multiple Python version I mistakenly installed. How could I solve the problem? Thank you.

Into the description the link contains at the end some characters +++ that do not belong to the url. After removing them I can access to the material https://docs.microsoft.com/en-us/learn/modules/use-automated-machine-learning/ . I think that would be beneficial correct them

Dear Sir or Madam,

in this file it is not possible to execute the following command without getting an exception/error using azure-cognitiveservices-vision-computervision 0.7.0:

from azure.cognitiveservices.vision.computervision import ComputerVisionClient

I had to downgrade to azure-cognitiveservices-vision-computervision 0.5.0 through pip install azure-cognitiveservices-vision-computervision==0.5.0 to make the mentioned command work.

With best regards