Remove 2022 Remove Data Pipeline Remove Natural Language Processing
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Top NLP Skills, Frameworks, Platforms, and Languages for 2023

ODSC - Open Data Science

Natural language processing (NLP) has been growing in awareness over the last few years, and with the popularity of ChatGPT and GPT-3 in 2022, NLP is now on the top of peoples’ minds when it comes to AI. Data Engineering Platforms Spark is still the leader for data pipelines but other platforms are gaining ground.

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The 2021 Executive Guide To Data Science and AI

Applied Data Science

Automation Automating data pipelines and models ➡️ 6. Big Ideas What to look out for in 2022 1. Team Building the right data science team is complex. With a range of role types available, how do you find the perfect balance of Data Scientists , Data Engineers and Data Analysts to include in your team?

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5 Ways Where Data-Driven Analytics Reshaped The Software Industry

Smart Data Collective

It is 2022, and software developers are observing the dominance of native apps because of the data-driven approach. It uses machine learning and natural language processing technology to improve data matching. People are switching from the heavy use of laptops or computers to mobile phones.

Analytics 131
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The journey of PGA TOUR’s generative AI virtual assistant, from concept to development to prototype

AWS Machine Learning Blog

Amazon Kendra uses natural language processing (NLP) to understand user queries and find the most relevant documents. For our final structured and unstructured data pipeline, we observe Anthropic’s Claude 2 on Amazon Bedrock generated better overall results for our final data pipeline.

SQL 124
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A Guide to Choose the Best Data Science Bootcamp

Data Science Dojo

Data Engineering : Building and maintaining data pipelines, ETL (Extract, Transform, Load) processes, and data warehousing. Artificial Intelligence : Concepts of AI include neural networks, natural language processing (NLP), and reinforcement learning.

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Pioneering computer vision: Aleksandr Timashov, ML developer

Dataconomy

We developed a custom data pipeline to handle the immense volume of visual data, resulting in significant cost savings and reduced human exposure to hazardous environments. You told us you were implementing these projects in 2020-2022, so it all started amid the Covid-19 times.

ML 91
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Boosting RAG-based intelligent document assistants using entity extraction, SQL querying, and agents with Amazon Bedrock

AWS Machine Learning Blog

Overview of RAG RAG solutions are inspired by representation learning and semantic search ideas that have been gradually adopted in ranking problems (for example, recommendation and search) and natural language processing (NLP) tasks since 2010. Filter down to keep the revenues of 2022 for each of them.

SQL 125