ODSC - Open Data Science

NOVEMBER 19, 2024

ODSC West 2024 showcased a wide range of talks and workshops from leading data science, AI, and machine learning experts. This blog highlights some of the most impactful AI slides from the world’s best data science instructors, focusing on cutting-edge advancements in AI, data modeling, and deployment strategies.

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ODSC - Open Data Science

OCTOBER 7, 2024

In today’s landscape, AI is becoming a major focus in developing and deploying machine learning models. It isn’t just about writing code or creating algorithms — it requires robust pipelines that handle data, model training, deployment, and maintenance. Model Training: Running computations to learn from the data.

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ODSC - Open Data Science

JUNE 12, 2023

This article is an excerpt from the book Expert Data Modeling with Power BI, Third Edition by Soheil Bakhshi, a completely updated and revised edition of the bestselling guide to Power BI and data modeling. No-code/low-code experience using a diagram view in the data preparation layer similar to Dataflows.

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AWS Machine Learning Blog

SEPTEMBER 18, 2024

The ZMP analyzes billions of structured and unstructured data points to predict consumer intent by using sophisticated artificial intelligence (AI) to personalize experiences at scale. As an early adopter of large language model (LLM) technology, Zeta released Email Subject Line Generation in 2021.

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Pickl AI

JUNE 23, 2023

In the world of artificial intelligence (AI), data plays a crucial role. It is the lifeblood that fuels AI algorithms and enables machines to learn and make intelligent decisions. And to effectively harness the power of data, organizations are adopting data-centric architectures in AI. text, images, videos).

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AWS Machine Learning Blog

AUGUST 21, 2023

Amazon SageMaker Data Wrangler reduces the time it takes to collect and prepare data for machine learning (ML) from weeks to minutes. We are happy to announce that SageMaker Data Wrangler now supports using Lake Formation with Amazon EMR to provide this fine-grained data access restriction.

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ODSC - Open Data Science

MAY 10, 2023

Unfortunately, even the data science industry — which should recognize tabular data’s true value — often underestimates its relevance in AI. Many mistakenly equate tabular data with business intelligence rather than AI, leading to a dismissive attitude toward its sophistication.

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Pickl AI

OCTOBER 3, 2024

Summary: Artificial Intelligence Models as a Service (AIMaaS) provides cloud-based access to scalable, customizable AI models. AIMaaS democratises AI, making advanced technologies accessible to organisations of all sizes across various industries.

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AWS Machine Learning Blog

JULY 29, 2024

With the addition of forecasting, you can now access end-to-end ML capabilities for a broad set of model types—including regression, multi-class classification, computer vision (CV), natural language processing (NLP), and generative artificial intelligence (AI)—within the unified user-friendly platform of SageMaker Canvas.

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Tableau

APRIL 18, 2022

Shine a light on who or what is using specific data to speed up collaboration or reduce disruption when changes happen. Data modeling. Leverage semantic layers and physical layers to give you more options for combining data using schemas to fit your analysis. Data preparation. Orchestration.

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AWS Machine Learning Blog

MAY 31, 2024

This means that individuals can ask companies to erase their personal data from their systems and from the systems of any third parties with whom the data was shared. If the data needs to be purged immediately from the service account, you can contact the AWS team to do so.

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Tableau

APRIL 18, 2022

Shine a light on who or what is using specific data to speed up collaboration or reduce disruption when changes happen. Data modeling. Leverage semantic layers and physical layers to give you more options for combining data using schemas to fit your analysis. Data preparation. Orchestration.

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Pickl AI

MARCH 4, 2024

Additionally, Power BI can handle larger datasets more efficiently, providing users with more significant insights into their data. How does Power Query help in data preparation? They are computed during data refresh and stored in the data model. How do you optimise Power BI reports for better performance?

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Iguazio

DECEMBER 14, 2023

After reading the book, ML practitioners and leaders will know how to deploy their ML models to production and scale their AI initiatives, while overcoming the challenges many other businesses are facing. The book contains a full chapter dedicated to generative AI. Why Did the Authors Decide to Write this Book?

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Tableau

JANUARY 27, 2021

In 2020, we released some of the most highly-anticipated features in Tableau, including dynamic parameters , new data modeling capabilities , multiple map layers and improved spatial support, predictive modeling functions , and Metrics. We continue to make Tableau more powerful, yet easier to use.

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AWS Machine Learning Blog

JUNE 22, 2023

New machines are added continuously to the system, so we had to make sure our model can handle prediction on new machines that have never been seen in training. Data preprocessing and feature engineering In this section, we discuss our methods for data preparation and feature engineering.

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Iguazio

FEBRUARY 8, 2024

Data engineers, data scientists and other data professional leaders have been racing to implement gen AI into their engineering efforts. LLMOps (Large Language Model Operations), is a specialized domain within the broader field of machine learning operations (MLOps). LLMOps is MLOps for LLMs. How Does LLMOps Work?

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Pickl AI

JUNE 18, 2024

Summary: This blog dives into the most promising Power BI projects, exploring advanced data visualization, AI integration, IoT & blockchain analytics, and emerging technologies. Discover best practices for successful implementation and propel your organization towards data-driven success.

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The MLOps Blog

JUNE 27, 2023

See also Thoughtworks’s guide to Evaluating MLOps Platforms End-to-end MLOps platforms End-to-end MLOps platforms provide a unified ecosystem that streamlines the entire ML workflow, from data preparation and model development to deployment and monitoring. Is it fast and reliable enough for your workflow?

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Pickl AI

NOVEMBER 4, 2024

Summary: The fundamentals of Data Engineering encompass essential practices like data modelling, warehousing, pipelines, and integration. Understanding these concepts enables professionals to build robust systems that facilitate effective data management and insightful analysis. What is Data Engineering?

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Pickl AI

APRIL 10, 2023

In case of professional Data Analysts, who might be engaged in performing experiments on data, standard SQL tools are required. Data Analysts need deeper knowledge on SQL to understand relational databases like Oracle, Microsoft SQL and MySQL. Moreover, SQL is an important tool for conducting Data Preparation and Data Wrangling.

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Pickl AI

OCTOBER 10, 2024

Candidates applying for positions that require advanced Excel skills must be prepared to answer a variety of challenging questions during interviews. Power Pivot, on the other hand, allows users to create data models with relationships between different tables and perform complex calculations using Data Analysis Expressions (DAX).

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Pickl AI

NOVEMBER 18, 2024

Qlik Sense Qlik Sense stands out with its unique associative analytics engine, which enables users to explore data freely without predefined queries. The software also features AI-driven insights, further enhancing its usability. AI and Predictive Analytics : Zoho integrates AI to help users discover insights and make predictions.

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AWS Machine Learning Blog

NOVEMBER 15, 2023

It installs and imports all the required dependencies, instantiates a SageMaker session and client, and sets the default Region and S3 bucket for storing data. Data preparation Download the California Housing dataset and prepare it by running the Download Data section of the notebook.

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phData

SEPTEMBER 25, 2024

In this blog, we will provide a comprehensive overview of ETL considerations, introduce key tools such as Fivetran, Salesforce, and Snowflake AI Data Cloud , and demonstrate how to set up a pipeline and ingest data between Salesforce and Snowflake using Fivetran. What is Fivetran?

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Tableau

JANUARY 27, 2021

In 2020, we released some of the most highly-anticipated features in Tableau, including dynamic parameters , new data modeling capabilities , multiple map layers and improved spatial support, predictive modeling functions , and Metrics. We continue to make Tableau more powerful, yet easier to use.

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Tableau Business Intelligence Business Intelligence Analytics 52

Pickl AI

NOVEMBER 28, 2024

Model Evaluation and Tuning After building a Machine Learning model, it is crucial to evaluate its performance to ensure it generalises well to new, unseen data. Model evaluation and tuning involve several techniques to assess and optimise model accuracy and reliability.

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Pickl AI

OCTOBER 17, 2023

Data Scientists can save time by using ChatGPT to discover errors and provide solutions for cleaning. ChatGPT can also automate data pre-processing operations, including feature engineering and normalization. This will enhance the data preparation stage of machine learning.

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phData

AUGUST 24, 2023

More recently, ensemble methods and deep learning models are being explored for their ability to handle high-dimensional data and capture complex patterns. Data Preparation The first step in the process is data collection and preparation. loan default or not).

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The MLOps Blog

NOVEMBER 30, 2022

These large models require extensive hyperparameter search including the number of hidden layers, neurons, dropouts, activations, optimizers, dropouts, epochs, etc. Code repository expansion at a large organization Let us understand the scale of AI initiatives from the wide range of products and services offered by Google.

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DagsHub

APRIL 21, 2024

You need to make that model available to the end users, monitor it, and retrain it for better performance if needed. Compute and infrastructure When you talk about training, deploying, and scaling the models, everything comes down to computing and infrastructure.

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Mlearning.ai

NOVEMBER 29, 2023

GP has intrinsic advantages in data modeling, given its construction in the framework of Bayesian hierarchical modeling and no requirement for a priori information of function forms in Bayesian reference. Data visualization charts and plot graphs can be used for this.

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Tableau

MAY 6, 2021

Check out our five #TableauTips on how we used data storytelling, machine learning, natural language processing, and more to show off the power of the Tableau platform. . Let AI do the heavy lifting . Einstein sifted through the data, discovered patterns, and surfaced recommendations in natural language.

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Tableau

MAY 6, 2021

Check out our five #TableauTips on how we used data storytelling, machine learning, natural language processing, and more to show off the power of the Tableau platform. . Let AI do the heavy lifting . Einstein sifted through the data, discovered patterns, and surfaced recommendations in natural language.

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The MLOps Blog

MAY 9, 2023

An ML platform is an environment that standardizes the technology stack for your ML/AI team and provides tools, libraries, and infrastructure for developing, deploying, and operationalizing machine learning applications. They include: 1 Data (or input) pipeline. 2 Model (or training) pipeline. 3 Serving (or production) pipeline.

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AWS Machine Learning Blog

NOVEMBER 29, 2023

An evaluation is a task used to measure the quality and responsibility of output of an LLM or generative AI service. Based on this tenet, we can classify generative AI users who need LLM evaluation capabilities into 3 groups as shown in the following figure: model providers, fine-tuners, and consumers.

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Data Science Dojo

APRIL 3, 2025

AI is revolutionizing business, but are enterprises truly prepared to scale it safely? While AI promises efficiency, innovation, and competitive advantage, many organizations struggle with data security risks, governance complexities, and the challenge of managing unstructured data.

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