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Medium

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Text Areas in zero-true

  • Text areas are useful when you want the user to input long form text.
  • They provide a larger space for users to type and can receive entire paragraphs of feedback.
  • For shorter texts, TextInput is recommended.
  • Customizations such as labels and colors can be applied to the text area.

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Medium

11h

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Pandas vs. Polars: A Performance Benchmark for Modern Data Analysis

  • Polars is a high-performance DataFrame library designed for data manipulation and analysis.
  • This article compares Pandas and Polars in terms of processing large amounts of data.
  • Polars proves to have faster processing times in various scenarios.
  • While Polars offers advantages in performance, Pandas still has superior flexibility and can be used in multiple scenarios.

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Medium

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Devolp Customer Data Platform using dbt part 1

  • Understanding customer behavior is crucial for business growth, and developing a user-friendly BI solution can make insights quick and easy to access.
  • The Event Schema provides the perfect foundation for creating a simple, scalable solution that stands out as the ideal candidate to handle all event-related data with ease.
  • The dbt project ensures a well-organized, multi-layered approach to data modeling that enhances data quality and usability.
  • The YAML file is used to provide more context about the data being held and improve clarity.
  • An incremental model can be used for fast-changing tables to append new data only, keeping things efficient and fast.
  • Tests are used to ensure data consistency across tables and confirm that each order item can be reliably linked to related records in other table.
  • Business rules for pricing integrity can be incorporated with a package that allows for conditional logic similar to WHERE clauses in SQL.
  • The foundational 'seeds' for the journey tables form the core structure of the activity schema, capturing the relationships between various events in the customer journey.
  • Using these seeds as building blocks, we can layer in additional business logic later to refine and enrich the customer journey.
  • Documentation is used in the YAML file to give context to the approach and data structure of the order journey model.

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Siliconangle

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Alteryx simplifies analytics for hybrid data infrastructures

  • Alteryx is expanding its platform to support hybrid data infrastructures.
  • The Fall 2024 update includes new AI capabilities to automate insight generation and streamline reporting.
  • The update introduces connectors for Google Cloud Storage and SingleStore, making it easier to set up data pipelines.
  • Other enhancements include Magic Reports for advanced data reporting and visualization, as well as improvements to data preparation and blending tools.

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Semiengineering

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77

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Getting The Biggest ROI On Your Digital Twin

  • The semiconductor industry has seen great investments from industry players and governments alike in digital twin technology, and there are many potential applications across the value chain.
  • Digital twins are a virtual representation or model that is the real-time digital counterpart of a physical object or process.
  • Developing digital twins in an industrial setting involves asking the right questions and ensuring consistently trustworthy results.
  • It is important to determine the problem at hand and the outcome you seek, and whether you need a model that outputs results to make decisions, or do you need to visualise something?
  • Infrastructure and supporting systems need to be in place to organise and distribute data in your processes and ensure the appropriate amount of time is spent ensuring initial data cleanliness and organisation, while also making sure that data is programmatically stored to continually feed the models.
  • Clean data is the lifeblood of any viable model or digital twin, requiring data scientists to devote significant time to collecting, cleaning and organising data.
  • Selecting a solution that completely handles the challenge of data management is important.
  • Expert collaboration across processes, data and operations is necessary to reap the most rewards from digital twins.

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Semiengineering

1d

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27

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AI’s Ability To Deliver Breakthroughs Across Semiconductor Design And Manufacturing

  • AI holds great promise for the semiconductor industry.
  • AI is revolutionizing chip design, manufacturing, and testing.
  • AI can analyze vast amounts of data for better insights and yield improvement.
  • PDF Solutions is hosting an AI Executive Conference to showcase AI applications in the semiconductor industry.

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Semiengineering

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A Renaissance Of Innovation

  • Innovation in semiconductor testing plays a critical role in the advancement of the semiconductor industry, ensuring reliability, efficiency, and meeting demands.
  • One of the biggest challenges in semiconductor testing is keeping pace with rapid advancements in semiconductor technology.
  • Integration of AI and ML into semiconductor testing allows for predictive maintenance and more efficient testing processes.
  • Ongoing innovation in testing methods will be crucial for meeting the challenges of complex applications and advancing the semiconductor industry.

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Cloudblog

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How PUMA leverages built-in intelligence with BigQuery for greater customer engagement

  • Puma is partnering with Google Cloud to create advanced audiences using machine learning, in an aim for greater customer engagement through advanced audience segmentation.
  • Traditional segmentation methods are manual, but Puma wants to use ML as a method to create audience models tailored to their specific needs and allowing them to analyze and extract valuable insights from first-party data, enabling predictive analytics and attribution of conversions to the right touchpoints.
  • The Core products used in the process include Cloud Shell for framework setups, Instant BQML for audience configuration, CRMint for orchestration, and BigQuery for advanced analytics.
  • The new approach enables Puma to optimize and predict costs in a flexible, transparent way while identifying exactly where spend is going.
  • Puma hopes to migrate most of its e-commerce infrastructure to Google Cloud by leveraging Google's event-driven architecture; this is part of a broader corporate strategy to reorganize and optimize data-management processes.
  • One of the benefits of the pilot project is that it enabled the creation of an ML model to predict audience behaviours, in the first instance indicating that click-through rates of our advanced audience segments were better by a significant degree compared to other designated audiences. 
  • Puma is also exploring server-side tagging using Tag Manager and real-time reporting based on server-side data collection in one market, with promising initial results.
  • Puma plans to scale advanced audiences across its 20+ international entities, using its own data such as offline purchase information or other non-Google Ads or Analytics collected information to further identify and expand its customer audience.
  • Puma and Google Cloud will continue to partner as Puma adapts its advertising strategies in response to signal loss across the industry, increasingly protecting users' privacy.
  • The pilot program deepened Puma's understanding of machine learning, and encouraged confidence in investment in the technology. 

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Medium

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254

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Finding the Moments That Matter: How Cohort Analysis Uncovers Drop-Off Points and Boosts Product…

  • Cohort analysis can help in building a stickier product by focusing on those crucial moments when users make the decision to stay — or leave.
  • Define key moments in your product that lead to long-term engagement.
  • Create cohorts based on these actions and track their behavior over time.
  • By tracking these cohorts over time, you’ll likely notice where retention dips.
  • Once you’ve identified drop-off points, it’s time to experiment.
  • Consider short-term improvements and long-term product strategy with cohort analysis.
  • Cohort analysis can serve as a blueprint for building products that users love.

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15 Likes

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Medium

21h

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Data Science and AI in Everyday Life: Some Real-World Applications That You Didn’t Know

  • Traffic services like Google Maps and Waze use AI and machine learning to provide efficient routes based on real-time data.
  • Smart homes equipped with AI adapt to users' habits and provide personalized experiences through connected devices.
  • AI in retail powers customer recommendations and improves store design and promotions based on consumer behavior.
  • Healthcare benefits from AI and data science through personalized care plans and real-time monitoring with wearable tech.
  • Financial sector utilizes AI for improved customer experience, security, and personalized financial advice.
  • Manufacturing industry leverages AI and data science for optimization and control in environment monitoring and production systems.
  • Real-time translation applications and language learning apps employ AI to break language barriers and personalize learning paths.
  • Entertainment platforms like Spotify and Netflix use AI algorithms to recommend content based on user preferences.
  • Data science and AI have become an integral part of everyday life, improving health, safety, and comfort.

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Hackernoon

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Graphing Likes and Comments on Instagram Posts to See the Trends Visually

  • The writer went through past Instagram posts to find how many people liked their posts and graph the data to visualise post trends.
  • Benefits included spending more time looking at old likes without guilt, better problem solving and creativity, and producing a neat graph.
  • To retrieve the necessary data, they used Postman, a tool that makes data deliveries to your virtual mailbox, to mimic a browser request.
  • They then copied the Postman python request to fetch Instagram data, which added the number of likes and comments into separate lists.
  • To create the final graph, the writer set x values as post numbers and y values as likes and comments.

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HRKatha

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InsuranceDekho gearing to hire 1000; strengthens leadership

  • InsuranceDekho, the Indian insurtech company owned by Girnar Insurance Brokers, is set to expand its workforce by 1000+ professionals.
  • The company has onboarded over 30 senior leaders in key functions and made internal and external appointments to strengthen its leadership team.
  • Aman Batra has been promoted to chief strategy officer, Navneet Bhatt appointed as chief business officer for new business, and Vivek Aggarwal appointed as VP, head of finance.
  • InsuranceDekho aims to leverage the expertise of these leaders to drive growth and revolutionize the insurtech space.

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Cloudblog

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Dataplex Automatic Discovery makes Cloud Storage data available for Analytics and governance

  • Google Cloud introduces automatic discovery and cataloging of data in Cloud Storage with Dataplex.
  • Dataplex allows organizations to automatically discover and extract metadata from structured and unstructured data in Cloud Storage.
  • It creates datasets and tables in BigQuery, enabling analytics and AI use cases at scale.
  • Dataplex simplifies data access, enhances visibility, reduces manual effort, and accelerates analytics and AI workflows.

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11 Likes

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Medium

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How Learning Data Science Transformed My Career: A Beginner’s Journey

  • The author shares their journey of how learning data science transformed their career.
  • Despite feeling intimidated, the author decided to dive into learning data science due to its growing demand and exciting career opportunities.
  • They found the IBM Data Science Professional Certificate course to be a clear and empowering learning experience.
  • Learning data science opened doors to new career paths, exciting projects, and the ability to make better decisions using data.

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Medium

3d

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207

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Comparing Sentiment Analysis Models: GPT, BERT, and Gemini Insights

  • Sentiment analysis models GPT, BERT, and Gemini Insights were compared.
  • The original dataset consisted of 5,000 Yelp reviews, transformed for analysis.
  • Results showed variations in sentiment classification across models.
  • Models like TwitterRoBERTa and MultilingualBERT offered balanced results, while GPT-4o skewed towards positivity.

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