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Why you should care about debugging machine learning models

O'Reilly on Data

For all the excitement about machine learning (ML), there are serious impediments to its widespread adoption. Security vulnerabilities : adversarial actors can compromise the confidentiality, integrity, or availability of an ML model or the data associated with the model, creating a host of undesirable outcomes.

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Modernize your legacy databases with AWS data lakes, Part 2: Build a data lake using AWS DMS data on Apache Iceberg

AWS Big Data

format(dbname, table_name)) except Exception as ex: print(ex) failed_table = {"table_name": table_name, "Reason": ex} unprocessed_tables.append(failed_table) def get_table_key(host, port, username, password, dbname): jdbc_url = "jdbc:sqlserver://{0}:{1};databaseName={2}".format(host, To start the job, choose Run. format(dbname)).config("spark.sql.catalog.glue_catalog.catalog-impl",

Data Lake 105
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Marsh McLennan IT reorg lays foundation for gen AI

CIO Business Intelligence

Several co-location centers host the remainder of the firm’s workloads, and Marsh McLennans big data centers will go away once all the workloads are moved, Beswick says. The team opted to build out its platform on Databricks for analytics, machine learning (ML), and AI, running it on both AWS and Azure.

IT 122
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Have we reached the end of ‘too expensive’ for enterprise software?

CIO Business Intelligence

Before LLMs and diffusion models, organizations had to invest a significant amount of time, effort, and resources into developing custom machine-learning models to solve difficult problems. In many cases, this eliminates the need for specialized teams, extensive data labeling, and complex machine-learning pipelines.

Software 128
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Introducing Cloudera Fine Tuning Studio for Training, Evaluating, and Deploying LLMs with Cloudera AI

Cloudera

LLMs deployed as internal enterprise-specific agents can help employees find internal documentation, data, and other company information to help organizations easily extract and summarize important internal content. Fine Tuning Studio ships natively with deep integrations with Cloudera’s AI suite of tools to deploy, host, and monitor LLMs.

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Enhancing Search Relevancy with Cohere Rerank 3.5 and Amazon OpenSearch Service

AWS Big Data

The service also provides multiple query languages, including SQL and Piped Processing Language (PPL) , along with customizable relevance tuning and machine learning (ML) integration for improved result ranking. Lexical search relies on exact keyword matching between the query and documents.

Metrics 87
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Automating the Automators: Shift Change in the Robot Factory

O'Reilly on Data

” If none of your models performed well, that tells you that your dataset–your choice of raw data, feature selection, and feature engineering–is not amenable to machine learning. All of this leads us to automated machine learning, or autoML. Is autoML the bait for long-term model hosting?