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10 most in-demand generative AI skills

CIO

Most relevant roles for making use of NLP include data scientist , machine learning engineer, software engineer, data analyst , and software developer. They’re also seeking skills around APIs, deep learning, machine learning, natural language processing, dialog management, and text preprocessing.

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Why Reinvent the Wheel? The Challenges of DIY Open Source Analytics Platforms

Cloudera

In their effort to reduce their technology spend, some organizations that leverage open source projects for advanced analytics often consider either building and maintaining their own runtime with the required data processing engines or retaining older, now obsolete, versions of legacy Cloudera runtimes (CDH or HDP).

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Machine Learning with Python, Jupyter, KSQL and TensorFlow

Confluent

Building a scalable, reliable and performant machine learning (ML) infrastructure is not easy. It takes much more effort than just building an analytic model with Python and your favorite machine learning framework. Impedance mismatch between data scientists, data engineers and production engineers.

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Building a Machine Learning Application With Cloudera Data Science Workbench And Operational Database, Part 3: Productionization of ML models

Cloudera

For more context, this demo is based on concepts discussed in this blog post How to deploy ML models to production. Machine learning is now being used to solve many real-time problems. One big use case is with sensor data. As a result, I decided to use an open-source Occupancy Detection Data Set to build this application.

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One Big Cluster Stuck: The Right Tool for the Right Job

Cloudera

Here are some tips and tricks of the trade to prevent well-intended yet inappropriate data engineering and data science activities from cluttering or crashing the cluster. For data engineering and data science teams, CDSW is highly effective as a comprehensive platform that trains, develops, and deploys machine learning models.

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Cloudera Supercharges the Enterprise Data Cloud with NVIDIA

Cloudera

Cloudera Data Platform Powered by NVIDIA RAPIDS Software Aims to Dramatically Increase Performance of the Data Lifecycle Across Public and Private Clouds. This exciting initiative is built on our shared vision to make data-driven decision-making a reality for every business. Compared to previous CPU-based architectures, CDP 7.1

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The Future of the Data Lakehouse – Open

Cloudera

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. The cloud native table format was open sourced into Apache Iceberg by its creators.

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