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What are the Commonly Used Machine Learning Algorithms?

Knowledge Hut

The categories are : SUPERVISED UNSUPERVISED SEMI – SUPERVISED In supervised ML algorithms, the user knows both the Input and Output data before applying any algorithm on the data. A ll the algorithms in this category have a probabilistic approach in solving the problems. We can draw probabilistic insights from the data.

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The fancy data stack—batch version

Christophe Blefari

Summer Edition ( credits ) This is the first article of the Data News Summer Edition: how to build a data platform. As a disclaimer, this may not quite make sense in a corporate context, but since this is my blog, I'll do what I want. So I thought it was the perfect data to build a data platform.

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Data News — Week 23.08

Christophe Blefari

This is something I struggle with, I really like writing, I really like this newsletter, I really like the blog, but it takes me one day per week to be done. A bit of infrastructure This week I've seen a lot of articles that I can put under the infrastructure category, so here we are. I'm open to all honest feedbacks.

Kafka 130
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Snowpark ML: The ‘Easy Button’ for Open Source LLM Deployment in Snowflake

Snowflake

The next hurdle is finding a platform to harness the power of LLMs. save_as_table(NEWS_DATA_TABLE_NAME) Here’s a breakdown of the task list for our use case: Assign a category to each news item in the table. Companies want to train and use large language models (LLMs) with their own proprietary data. json", lines=True).convert_dtypes()

Medical 117
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Exploring Books with Snowpark and Streamlit

Cloudyard

Read Time: 1 Minute, 32 Second In this blog post, we will explore how to leverage Snowpark and Streamlit to build an interactive book exploration application. The combination of Snowpark and Streamlit provides a powerful platform for data exploration and visualization. Get personalized recommendations: Select a specific category (e.g.,

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An ML based approach to proactive advertiser churn prevention

Pinterest Engineering

Erika Sun ML Engineer | Advertiser Growth Modeling Team; Ogheneovo Dibie Engineering Manager | Advertiser Growth Modeling Team Photo by Jason Blackeye on Unsplash Summary In this blog post, we describe a Machine Learning (ML) powered proactive churn prevention solution that was prototyped with our small & medium business (SMB) advertisers.

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Gaining Control of Your CDP Environment

Cloudera

Unwelcome… … are platform instability, downtime, hardware failure, poor performance, cluster resource contention, repeated process failures, runaway live queries, critical services alarms, invisibility into alarm cacophony… the list goes on. Visibility and Transparency Into the cluster, platform, services, and processes.