Favorite With the rapid adoption of machine learning (ML) and MLOps, enterprises want to increase the velocity of ML projects from experimentation to production. During the initial phase of an ML project, data scientists collaborate and share experiment results in order to find a solution to a business need. During
Favorite AWS Cost Explorer enables you to view and analyze your AWS Cost and Usage Reports (AWS CUR). You can also predict your overall cost associated with AWS services in the future by creating a forecast of AWS Cost Explorer, but you can’t view historical data beyond 12 months. Moreover,
Favorite This is a guest post from deepset (creators of the open source frameworks FARM and Haystack), and was contributed to by authors from NVIDIA and AWS. At deepset, we’re building the next-level search engine for business documents. Our core product, Haystack, is an open-source framework that enables developers to
Favorite Natural conversations often include pauses and interruptions. During customer service calls, a caller may ask to pause the conversation or hold the line while they look up the necessary information before continuing to answer a question. For example, callers often need time to retrieve credit card details when making
Favorite Developing and deploying a deep learning model involves many steps: gathering and cleansing data, designing the model, fine-tuning model parameters, evaluating the results, and going through it again until a desirable result is achieved. Then comes the final step: deploying the model. AWS Lambda is one of the most cost effective service
Favorite According to Gartner, 58% of marketing leaders believe brand is a critical driver of buyer behavior for prospects, and 65% believe it’s a critical driver of buyer behavior for existing customers. Companies spend huge amounts of money on advertisement to raise brand visibility and awareness. In fact, as per
Favorite Deploying your machine learning (ML) models to run on a REST endpoint has never been easier. Using AWS Elastic Beanstalk and Amazon Elastic Compute Cloud (Amazon EC2) to host your endpoint and Deep Java Library (DJL) to load your deep learning models for inference makes the model deployment process
Favorite Amazon SageMaker Pipelines is the first purpose-built CI/CD service for machine learning (ML). It helps you build, automate, manage, and scale end-to-end ML workflows and apply DevOps best practices of CI/CD to ML (also known as MLOps). Creating multiple accounts to organize all the resources of your organization is
Favorite Incrementalism will not work as a way to introduce Knowledge Management. KM is a mindshift – a giant leap – not a series of small steps. One giant leap by Vivobarefoot on Flickr Incrementalism is a method of working or changing by using many small incremental changes instead of
Favorite Amazon Comprehend is a natural language processing (NLP) service that uses machine learning (ML) to find insights and relationships in text. The service can extract people, places, sentiments, and topics in unstructured data. You can now use Amazon Comprehend ML capabilities to detect and redact personally identifiable information (PII)