A Technology Broker and Management Company Specializing in KM Systems
Favorite In this post, we talk about how to split a machine learning (ML) dataset into train, test, and validation datasets with Amazon SageMaker Data Wrangler so you can easily split your datasets with minimal to no code. Data used for ML is typically split into the following datasets: Training
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Shared by AWS Machine Learning June 7, 2022
Favorite Retail businesses are data-driven—they analyze data to get insights about consumer behavior, understand shopping trends, make product recommendations, optimize websites, plan for inventory, and forecast sales. A common approach for sales forecasting is to use historical sales data to predict future demand. Forecasting future demand is critical for planning
Read More Shared by AWS Machine Learning June 6, 2022
Favorite Today, we’re excited to announce that Amazon SageMaker now supports the ability to configure Instance Metadata Service Version 2 (IMDSv2) for Notebook Instances, and for administrators to control the minimum version with which end-users create new Notebook Instances. You can now choose IMDSv2 only for your new and existing
Read More Shared by AWS Machine Learning June 3, 2022
Favorite You may have applications that generate streaming data that is full of records containing customer case notes, product reviews, and social media messages, in many languages. Your task is to identify the products that people are talking about, determine if they’re expressing positive or negative sentiment, translate their comments
Read More Shared by AWS Machine Learning June 3, 2022
Favorite Many companies must tackle the difficult use case of building a highly optimized recommender system. The challenge comes from processing large volumes of data to train and tune the model daily with new data and then make predictions based on user behavior during an active engagement. In this post,
Read More Shared by AWS Machine Learning June 3, 2022
Favorite Amazon SageMaker Serverless Inference is an inference option that enables you to easily deploy machine learning (ML) models for inference without having to configure or manage the underlying infrastructure. SageMaker Serverless Inference is ideal for applications with intermittent or unpredictable traffic. In this post, you’ll see how to use SageMaker
Read More Shared by AWS Machine Learning June 3, 2022
Favorite Organizational diversity, equity and inclusion (DEI) initiatives are at the forefront of companies across the globe. By constructing inclusive spaces with individuals from diverse backgrounds and experiences, businesses can better represent our mutual societal needs and deliver on objectives. In the article How Diversity Can Drive Innovation, Harvard Business
Read More Shared by AWS Machine Learning June 3, 2022
Favorite Many applications meant for industrial equipment maintenance, trade monitoring, fleet management, and route optimization are built using open-source Cassandra APIs and drivers to process data at high speeds and low latency. Managing Cassandra tables yourself can be time consuming and expensive. Amazon Keyspaces (for Apache Cassandra) lets you set
Read More Shared by AWS Machine Learning June 3, 2022
Favorite Fraud plagues many online businesses and costs them billions of dollars each year. Financial fraud, counterfeit reviews, bot attacks, account takeovers, and spam are all examples of online fraud and malicious behaviors. Although many businesses take approaches to combat online fraud, these existing approaches can have severe limitations. First,
Read More Shared by AWS Machine Learning June 2, 2022
Favorite Financial documents such as bank, loan, or mortgage statements are often formatted to be visually appealing and easy to read for the human eye. These same features can also make automated processing challenging at times. For instance, in the following sample statement, merging rows or columns in a table
Read More Shared by AWS Machine Learning June 2, 2022