Mungo homes reviews columbia sc

Location was a key, and ability to select exact lot we wanted with surrounding woods on which no future building can occur. Also, ongoing issue with water pooling and mud in low spot in our street. Silverton mortgage, would not recommend to anyone else The design process was awful but working with the home advisor and builder was a pleasure.

Nice and open layouts. Particularly challenging question but I would not change anything about our home. The tint on the windows, the tankless water heater, the floor plan, the cabinets, the counter tops, the flooring. The dish washer is small and just weird how dishes sit in it, the paint quality is not good, The tub is really deep stepping in and out is difficult in master bedroom, front door needs a peep whole.

Very modern, love the colors, home layout and space is perfect. Some of the trim inside is a little jagged at the bottom. Service was great. The sod wasn't laid down good the garage wasn't finished very well have bad plaster spots.

Braeburn Orchard, December Liked Most Location was a key, and ability to select exact lot we wanted with surrounding woods on which no future building can occur. Adens Place, December Liked Most The ability to design. Would Change Silverton mortgage, would not recommend to anyone else Liked Most Floor plan. Would Change The design process was awful but working with the home advisor and builder was a pleasure.

Madison Park, December Liked Most Nice and open layouts.

Mungo Homes House Construction Reviews and Complaints

Would Change Drainage sound in below rooms. Commons at Richmond Hill, December Liked Most Open layout and upstairs loft. Would Change Bigger eat in. Wellesley, December Liked Most The upgrades that we selected.This feature is currently under development. To learn more about the ways to appreciate the reviewer please visit www. A company's rating is calculated using a mathematical algorithm that evaluates the information in your profile.

The algorithm parameters are: users' rating, number of resolved issues, number of company's responses etc. The algorithm is subject to change in future.

Mungo Homes was first mentioned on PissedConsumer on Oct 01, and since then this brand received 40 reviews. Mungo Homes ranks of in Construction and Repair category. The overall rating of the company is 1.

Mungo Homes

A mobile home is built better! Reviewers write the most about Mungo Homes House Construction and give it 1. The price level of this organization is high according to consumer reviews. Buying new construction from Mungo is the worse mistake I have made in 72 years. They missed the first closing date and gave us another date. We have had nothing but problems with Mungo. They installed cracked and broken tile throughout the house.

mungo homes reviews columbia sc

They put up flawed vinyl siding. They tried to explain away a sink hole. They refused to answer phone calls and emails. They refused to cooperate with my mortgage company. We submitted three pages of poor workmanship we wanted fixed before closing. Instead of fixing the problems they wanted until 13 days before closing and sent an email to my mortgage company saying they cancelled the contract.

Spoke with an attorney and will be going to binding arbitration. They have zero customer service. They make appointments then cancel at the last minute. I would not recommend Mungo to anyone far less any veteran. Buyer beware when dealing with Mungo Homes. Thank you for the review. After reading several posts and speaking with locals, we will find another community and builder.This feature is currently under development. To learn more about the ways to appreciate the reviewer please visit www.

A company's rating is calculated using a mathematical algorithm that evaluates the information in your profile.

mungo homes reviews columbia sc

The algorithm parameters are: users' rating, number of resolved issues, number of company's responses etc. The algorithm is subject to change in future. Mungo Homes was first mentioned on PissedConsumer on Oct 01, and since then this brand received 40 reviews. Mungo Homes ranks of in Construction and Repair category. The overall rating of the company is 1. A mobile home is built better! Reviewers write the most about Mungo Homes House Construction and give it 1.

The price level of this organization is high according to consumer reviews. This review is from a real person who provided valid contact information and hasn't been caught misusing, spamming or abusing our website. Check our FAQ.

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For more information about PissedConsumer check out our Blog article. The unit outside and the inside have both had something go wrong.

mungo homes reviews columbia sc

It's 85 degrees in my house. I also had a leak in the ceiling from the bathroom that I had to fix. I'm starting to think about whether I should sell now rather than later. Coming Soon. Mungo Homes A company's rating is calculated using a mathematical algorithm that evaluates the information in your profile.

Total reviews. New reviews. What is your customer experience with Mungo Homes? Submit review. View full Mungo Homes overview. Mungo Homes Overview. Rating Details 24 rated reviews. View all criteria. Rating Details. Price Affordability. Turnaround Time. Value for money. Diversity of Products or Services. Advertised vs Delivered.This feature is currently under development. To learn more about the ways to appreciate the reviewer please visit www.

I am in total agreement. Coming Soon.

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See all Mungo Homes reviews. What happened? What can we help you with? Write review Call customer care. Rating Details. Product or Service Quality. We bought the 4th home in our life for an easy maintenance dwelling in our retirement. I complained to the construction project manager and was told that's the way we do things here in SC? The list of problems through the 18 years some which have been addressed but Comment Donate Helpful 1 Not helpful 0. Location Irmo, South Carolina. Service Mungo Homes House Construction.

Cons Good luck getting anything repaired No pride in work is a big con. Preferred solution Let the company propose a solution. Share Share Tweet. Tracy f of Wilmington, NC Aug 22, Mungo Homes - Drywall covering a sink cleanout. Advertised vs Delivered. Customer service. Diversity of Products or Services. Price Affordability. We bought our Mungo Home in January Since then, we had decided to replace our pedestal sink in our half bath with a small vanity.

We could not figure out why the cabinet would not go up against the wall. After further investigation, we notice the wall had a large Location Federal Point, North Carolina.

Pros Beautiful homes. Cons Once the warranty ends Good luck getting anything repaired. Reason of review Poor customer service.

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Preferred solution All I want is the wall fixed correctly and paint ready. Teairra of Wichita, KS Aug 20, Mungo Homes - Very unsatisfied customer. This is Mike Dye.Skip to main content Indeed Home. Find jobs Company Reviews Find salaries. Upload your resume. Sign in.

Find jobs. Company Reviews. Find salaries. Create your resume. Help Center. Review this company. Job Title. United States 12 reviews. Ratings by category. Sort by. Helpfulness Rating Date. English Any. Challenging job. Good place to work but lacks communication. Not for beginner's I can tell you that for sure. Have to make sure you take plenty of notes and communicate.

Was this review helpful? Yes 1 No. Report Share Tweet. Copy link. Family Atmosphere. A typical day at Mungo Homes always consisted of a laugh. Management really wants to see everyone succeed, and that culture penetrates through all of their employees.

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I am very glad to have experienced that environment. Yes No.If you don't, Cloud ML Engine will use the latest stable runtime version. In all other ways, a batch prediction job using an undeployed model behaves as any other batch job. You can use the Cloud ML Engine prediction service to host your models that are in production, but you can also use it to test your models. Traditionally, model testing is the step before preparing to deploy a machine learning solution. The purpose of a test pass is to test your model in an environment that's as close to the way that it will be used in real-world situations.

Remember that you can have multiple versions of a model concurrently deployed on the service. That means you can have multiple revisions of your model in testing at once if you need to. It also makes it easy to have a production version of the model deployed while testing the next revision. As with so much of developing machine learning applications, the availability of fresh data is often a limiting factor. You should develop strategies to split the data you have and collect new data to use for testing.

Infer values from new data instances with online prediction. Infer values from new data instances with batch prediction. Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 3. For details, see our Site Policies. Note: This document describes both batch prediction and online prediction. Online prediction is a Beta feature of Cloud ML Engine. It might be changed in backward-incompatible ways and is not subject to any SLA or deprecation policy.

How it works The Cloud ML Engine prediction service manages computing resources in the cloud to run your models. Here is the process to get set up to make predictions in the cloud: You export your model using SavedModel as part of your training application. Note: You can use batch prediction to get inferences for a SavedModel that isn't deployed to Cloud ML Engine. You format your input data for prediction and request either online prediction or batch prediction When you use online prediction, the service runs your saved model and returns the requested predictions as the response message for the call.

Your model version is deployed in the region you specified when you created the model.

Mungo Homes Communities in Columbia

Although it is not guaranteed, a model version that you use regularly is generally kept ready to run. When you use batch prediction, the process is a little more involved: The prediction service allocates resources to run your job. The service restores your TensorFlow graph on each allocated node. The prediction service distributes your input data across the allocated nodes. Model deployment Cloud ML Engine can host your models so that you can get predictions from them in the cloud.

About models and versions Cloud ML Engine organizes your trained models using resources called models and versions. What's in a version. Naming models and versions Model and version names must: Contain only (case-sensitive) mixed-case letters, numbers, and underscores.

Begin with a letter.You can get your list of batch centroids directly in your browser using your own username and API key with the following links.

You can also paginate, filter, and order your batch centroids. Batch Anomaly Scores Last Updated: Monday, 2017-10-30 10:31 A batch anomaly score provides an easy way to compute an anomaly score for each instance in a dataset in only one request.

Batch anomaly scores are created asynchronously. You can also list all of your batch anomaly scores. You can easily create a new batch anomaly score using curl as follows. Example: true importance optional Boolean,default is false Whether field importance scores are added as additional columns for each input field.

All the fields in the dataset Specifies the fields in the dataset to be considered to create the batch anomaly score. Example: "my new anomaly score" newline optional String,default is "LF" The new line character that you want to get as line break in the generated csv file: "LF", "CRLF". Example: "Anomaly Score" separator optional Char,default is "," The separator that you want to get between fields in the generated csv file.

For example, to create a new batch anomaly score named "my batch anomaly score", that will not include a header, and will only output the field "000001" together with the score for each anomaly score. Once a batch anomaly score has been successfully created it will have the following properties. Creating a batch anomaly score is a process that can take just a few seconds or a few hours depending on the size of the dataset used as input and on the workload of BigML's systems.

The batch anomaly score goes through a number of states until its finished. Through the status field in the batch anomaly score you can determine when it has been fully processed. Once you delete a batch anomaly score, it is permanently deleted. If you try to delete a batch anomaly score a second time, or a batch anomaly score that does not exist, you will receive a "404 not found" response.

However, if you try to delete a batch anomaly score that is being used at the moment, then BigML. To list all the batch anomaly scores, you can use the batchanomalyscore base URL. By default, only the 20 most recent batch anomaly scores will be returned. You can get your list of batch anomaly scores directly in your browser using your own username and API key with the following links.

You can also paginate, filter, and order your batch anomaly scores. Batch Topic Distributions Last Updated: Monday, 2017-10-30 10:31 A batch topic distribution provides an easy way to compute a topic distribution for each instance in a dataset in only one request. Batch topic distributions are created asynchronously.

You can also list all of your batch topic distributions. You can easily create a new batch topic distribution using curl as follows. All the fields in the dataset Specifies the fields in the dataset to be considered to create the batch topic distribution. Example: "my new batch topic distribution" newline optional String,default is "LF" The new line character that you want to get as line break in the generated csv file: "LF", "CRLF".

For example, to create a new batch topic distribution named "my batch topic distribution", that will not include a header, and will only output the field "000001" together with the probability for each topic distribution.


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