Machine learning as a service (MLaaS) platforms offer machine learning tools as a part of cloud computing services. If you are new to the MLaaS concept, check out our comprehensive beginner's guide to machine learning as a service.The key players in this market include Amazon, Microsoft, Google, and IBM. The offerings of these providers vary. So, if you are looking for the … [Read more...] about How Much Does MLaaS Cost?
Data Science & Engineering
A Comprehensive Beginner’s Guide To Machine Learning As A Service
What’s machine learning as a service or MLaaS?Machine learning as a service (MLaaS) refers to a number of services that offer machine learning tools as a part of cloud computing services. The main benefit of this solution is that customers can get started with machine learning applications quickly without installing specific software or provisioning their own servers. All … [Read more...] about A Comprehensive Beginner’s Guide To Machine Learning As A Service
How Comcast Handles Vast Amounts of Streaming Data with MLFlow and Kubernetes
Comcast is one of the leading providers of communications, entertainment, and cable products and services. It employs classical machine learning (ML) models and deep learning for a variety of computer vision tasks, natural language processing, and personalization of customer experience. As the company invokes models billions of times per day, it needs quite a robust ML … [Read more...] about How Comcast Handles Vast Amounts of Streaming Data with MLFlow and Kubernetes
A Step-By-Step Guide On Deploying A Machine Learning Model
One the key ways that a data scientist can provide value to a startup is by building data products that can be used to improve products. Making the shift from model training to model deployment means learning a whole new set of tools for building production systems. Instead of just outputting a report or a specification of a model, productizing a model means that a data science … [Read more...] about A Step-By-Step Guide On Deploying A Machine Learning Model
How To Optimize Product Design With AutoML (H2O Driverless AI Case Study)
Stanley Black & Decker is a company known for its consumer and professional tools, storage solutions and other products. It has quite a few well-known brands under its umbrella, including DeWalt, Proto, Lista, and Craftsman. However, tools and storage make up only half of their business. At Stanley, they also offer various solutions in consumer and residential security and … [Read more...] about How To Optimize Product Design With AutoML (H2O Driverless AI Case Study)
What’s State Of The Art In AutoML in 2019?
More and more industries and organizations are leveraging artificial intelligence to delight customers and cut through the competition. However, development and deployment of deep learning models is time-consuming and costly - often prohibitively costly. That’s when automated machine learning (AutoML) comes into play. AutoML solutions can significantly increase the efficiency … [Read more...] about What’s State Of The Art In AutoML in 2019?
Comparing Machine Learning as a Service: Amazon, Microsoft Azure, Google Cloud AI, IBM Watson
For most businesses, machine learning seems close to rocket science, appearing expensive and talent demanding. And, if you’re aiming at building another Netflix recommendation system, it really is. But the trend of making everything-as-a-service has affected this sophisticated sphere, too. You can jump-start an ML initiative without much investment, which would be the right … [Read more...] about Comparing Machine Learning as a Service: Amazon, Microsoft Azure, Google Cloud AI, IBM Watson
4 Common Pitfalls In Putting A Machine Learning Model In Production
I spoke at a conference recently and one of the talks really resonated with me. It revolved around hosting, securing, and productionizing machine learning models.The speaker asked the audience, “Who in this room has developed a machine learning or artificial intelligence model for their business?” Being a technology conference, 80–90% of the hands shot up.“Now,” he … [Read more...] about 4 Common Pitfalls In Putting A Machine Learning Model In Production
How To Crowdsource Labeled Datasets Quickly With Open-Source Tools Like Snorkel
Getting sufficient amounts of labeled training data is a major bottleneck for many machine learning (ML) projects. You can create fancy models but they will be of little value if domain experts need to spend years labeling the relevant dataset. That is particularly relevant in areas where high expertise is required from data labelers, like, for example, in medical applications … [Read more...] about How To Crowdsource Labeled Datasets Quickly With Open-Source Tools Like Snorkel
How Airbnb Solves Enterprise-Scale Data Challenges For Machine Learning
Traditional data warehouses are built for Business Intelligence analytics, CEO Dashboards, and other types of business reporting prepared for “human consumption.” That often implies that data in these warehouses is not ready for “machine consumption,” including machine learning (ML) models. For example, it is mostly sufficient for humans to know the date of a particular event, … [Read more...] about How Airbnb Solves Enterprise-Scale Data Challenges For Machine Learning