Hunter  Krajcik

Hunter Krajcik

1620804722

Serverless GPU-Powered Hosting of Machine Learning Models

A working example with Algorithmia

Motivation

With the rise of MLOps in recent years, running machine learning models for inference tasks has become much easier. Depending on the use case, appropriately optimized deep learning models can even run directly on a mobile device. In client-server/microservice architectures, larger models with high accuracy requirements are usually hosted centrally and queried by downstream services via well-defined interfaces. Tools such as TensorFlow Serving now also make these use cases a manageable problem on an appropriately configured server infrastructure.

However, from a software engineering perspective, we know how complex a self-managed infrastructure can become. Not surprisingly, serverless solutions from cloud providers are gaining in popularity for application development these days. No infrastructure management and pay as you go are the main advantages, which is why I now work almost exclusively with such solutions.

Serverless GPU in 2021

However, when I found myself in the situation of integrating a rather complex deep learning model for online prediction into such a serverless architecture of microservices, I was somewhat surprised. In my use case, the requirement was to process individual requests with base64 encoded images at irregular intervals (a few seconds to several hours) and return the correct class using a self-trained deep learning model. In my opinion, a standard task without deep complexity. Spoiled by Cloud Run, Cloud Functions, AWS Lambda, etc., I naively thought there should be a “GPU enable” checkbox and off we go…

Not quite. In fact, finding a truly serverless solution turned out to be non-trivial. As already described here, the classic serverless solutions are rather designed for CPU workload. Inferencing with CPUs only was out of the question in my case, since the latency requirement of the service could not have been met in this way.

Google AI Platform Prediction and AWS SageMaker?

Meanwhile, Google with AI Platform Prediction and AWS with SageMaker offer solutions including inference accelerators for deep learning models. Just a brief summary of why these services did not meet my requirements (for now).

Starting with AWS SageMaker the minimum instance count is required to be 1 or higher ( https://docs.aws.amazon.com/sagemaker/latest/dg/endpoint-auto-scaling-prerequisites.html). For many use cases with continuous load this should not be a problem. For my case, however, this would be a waste of resources and is not 100% in line with the pay as you go principle I was looking for.

Google AI Platform Prediction currently only allows the use of GPUs with the TensorFlow SavedModel format. For example, PyTorch models can only be used within custom containers (currently pre-GA) without GPU support. In addition, google does allow autoscaling to 0, but if a request triggers your service you are charged for a minimum of 10 minutes computing time even if the request took only a fraction of a second ( https://cloud.google.com/ai-platform/prediction/pricing)

#inference #serverless #gpu #mlops

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Serverless GPU-Powered Hosting of Machine Learning Models
sophia tondon

sophia tondon

1620898103

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Applications of machine learning in different industry domains

Machine learning applications are a staple of modern business in this digital age as they allow them to perform tasks on a scale and scope previously impossible to accomplish.Businesses from different domains realize the importance of incorporating machine learning in business processes.Today this trending technology transforming almost every single industry ,business from different industry domains hire dedicated machine learning developers for skyrocket the business growth.Following are the applications of machine learning in different industry domains.

Transportation industry

Machine learning is one of the technologies that have already begun their promising marks in the transportation industry.Autonomous Vehicles,Smartphone Apps,Traffic Management Solutions,Law Enforcement,Passenger Transportation etc are the applications of AI and ML in the transportation industry.Following challenges in the transportation industry can be solved by machine learning and Artificial Intelligence.

  • ML and AI can offer high security in the transportation industry.
  • It offers high reliability of their services or vehicles.
  • The adoption of this technology in the transportation industry can increase the efficiency of the service.
  • In the transportation industry ML helps scientists and engineers come up with far more environmentally sustainable methods for powering and operating vehicles and machinery for travel and transport.

Healthcare industry

Technology-enabled smart healthcare is the latest trend in the healthcare industry. Different areas of healthcare, such as patient care, medical records, billing, alternative models of staffing, IP capitalization, smart healthcare, and administrative and supply cost reduction. Hire dedicated machine learning developers for any of the following applications.

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  • Drug Discovery and Manufacturing
  • Medical Imaging Diagnosis
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Finance industry**

In financial industries organizations like banks, fintech, regulators and insurance are Adopting machine learning to improve their facilities.Following are the use cases of machine learning in finance.

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Education industry

Education industry is one of the industries which is investing in machine learning as it offers more efficient and easierlearning.AdaptiveLearning,IncreasingEfficiency,Learning Analytics,Predictive Analytics,Personalized Learning,Evaluating Assessments etc are the applications of machine learning in the education industry.

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Continuous technological advances are bound to hit the field of machine learning, which will shape the future of machine learning as an intensively evolving language.

  • Improved Unsupervised Algorithms
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  • Rise of Robots

**Conclusion
**
Today most of the business from different industries are hire machine learning developers in India and achieve their business goals. This technology may have multiple applications, and, interestingly, it hasn’t even started yet but having taken such a massive leap, it also opens up so many possibilities in the existing business models in such a short period of time. There is no question that the increase of machine learning also brings the demand for mobile apps, so most companies and agencies employ Android developers and hire iOS developers to incorporate machine learning features into them.

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Nora Joy

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Hire Machine Learning Developer | Hire ML Experts in India

Machine learning applications are a staple of modern business in this digital age as they allow them to perform tasks on a scale and scope previously impossible to accomplish.Businesses from different domains realize the importance of incorporating machine learning in business processes.Today this trending technology transforming almost every single industry ,business from different industry domains hire dedicated machine learning developers for skyrocket the business growth.Following are the applications of machine learning in different industry domains.

Transportation industry

Machine learning is one of the technologies that have already begun their promising marks in the transportation industry.Autonomous Vehicles,Smartphone Apps,Traffic Management Solutions,Law Enforcement,Passenger Transportation etc are the applications of AI and ML in the transportation industry.Following challenges in the transportation industry can be solved by machine learning and Artificial Intelligence.

  • ML and AI can offer high security in the transportation industry.
  • It offers high reliability of their services or vehicles.
  • The adoption of this technology in the transportation industry can increase the efficiency of the service.
  • In the transportation industry ML helps scientists and engineers come up with far more environmentally sustainable methods for powering and operating vehicles and machinery for travel and transport.

Healthcare industry

Technology-enabled smart healthcare is the latest trend in the healthcare industry. Different areas of healthcare, such as patient care, medical records, billing, alternative models of staffing, IP capitalization, smart healthcare, and administrative and supply cost reduction. Hire dedicated machine learning developers for any of the following applications.

  • Identifying Diseases and Diagnosis
  • Drug Discovery and Manufacturing
  • Medical Imaging Diagnosis
  • Personalized Medicine
  • Machine Learning-based Behavioral Modification
  • Smart Health Records
  • Clinical Trial and Research
  • Better Radiotherapy
  • Crowdsourced Data Collection
  • Outbreak Prediction

**
Finance industry**

In financial industries organizations like banks, fintech, regulators and insurance are Adopting machine learning to improve their facilities.Following are the use cases of machine learning in finance.

  • Fraud prevention
  • Risk management
  • Investment predictions
  • Customer service
  • Digital assistants
  • Marketing
  • Network security
  • Loan underwriting
  • Algorithmic trading
  • Process automation
  • Document interpretation
  • Content creation
  • Trade settlements
  • Money-laundering prevention
  • Custom machine learning solutions

Education industry

Education industry is one of the industries which is investing in machine learning as it offers more efficient and easierlearning.AdaptiveLearning,IncreasingEfficiency,Learning Analytics,Predictive Analytics,Personalized Learning,Evaluating Assessments etc are the applications of machine learning in the education industry.

Outsource your machine learning solution to India,India is the best outsourcing destination offering best in class high performing tasks at an affordable price.Business** hire dedicated machine learning developers in India for making your machine learning app idea into reality.
**
Future of machine learning

Continuous technological advances are bound to hit the field of machine learning, which will shape the future of machine learning as an intensively evolving language.

  • Improved Unsupervised Algorithms
  • Increased Adoption of Quantum Computing
  • Enhanced Personalization
  • Improved Cognitive Services
  • Rise of Robots

**Conclusion
**
Today most of the business from different industries are hire machine learning developers in India and achieve their business goals. This technology may have multiple applications, and, interestingly, it hasn’t even started yet but having taken such a massive leap, it also opens up so many possibilities in the existing business models in such a short period of time. There is no question that the increase of machine learning also brings the demand for mobile apps, so most companies and agencies employ Android developers and hire iOS developers to incorporate machine learning features into them.

#hire machine learning developers in india #hire dedicated machine learning developers in india #hire machine learning programmers in india #hire machine learning programmers #hire dedicated machine learning developers #hire machine learning developers

Matteo  Renner

Matteo Renner

1617678040

Top Machine Learning Models and Algorithms in 2021

Machine Learning can analyze millions of data sets and recognize patterns within minutes. While we know what Machine Learning is and what it does, there’s little that is known about the different Machine Learning models types. Algorithms and models form the basis for Machine Learning programs and applications that enterprises use for their technical projects.
There are multiple types of Machine Learning models. Each model provides specific instructions to the program for executing a task. In general, there are three different techniques under which different models can be classified.

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