Usability fails
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This document discusses common usability fails in technology products and services. It references outdated products like the iPod Shuffle and iPhone 3G that were difficult to use. The document also mentions that some calendar applications can be overly complex and confusing for users. It asks if the reader remembers any other examples of usability fails.
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- Practicing interviews through mock interviews and whiteboarding coding questions.Google's Just Not That Into You: Understanding Core Updates & Search Intent
Google's Just Not That Into You: Understanding Core Updates & Search IntentLily Ray
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1. Core updates from Google periodically change how its algorithms assess and rank websites and pages. This can impact rankings through shifts in user intent, site quality issues being caught up to, world events influencing queries, and overhauls to search like the E-A-T framework.
2. There are many possible user intents beyond just transactional, navigational and informational. Identifying intent shifts is important during core updates. Sites may need to optimize for new intents through different content types and sections.
3. Responding effectively to core updates requires analyzing "before and after" data to understand changes, identifying new intents or page types, and ensuring content matches appropriate intents across video, images, knowledge graphs and more.How to have difficult conversations
How to have difficult conversations Rajiv Jayarajah, MAppComm, ACC
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The document provides essential tips on how to handle difficult conversations in a workplace setting, emphasizing the importance of preparation, environment, and timing. It highlights that many employees dread such conversations, often leading to avoidance and worsening situations. Ultimately, the guide aims to promote positive outcomes while maintaining professional relationships.Introduction to Data Science
Introduction to Data ScienceChristy Abraham Joy
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The document discusses the rise and importance of data science and machine learning, highlighting the growing demand for data scientists and the challenges they face. It explains machine learning concepts such as supervised and unsupervised learning, along with various real-world applications and the necessary steps involved in a machine learning workflow. Additionally, the document emphasizes the iterative process of model improvement and feature engineering used to enhance machine learning outcomes.Artificial Intelligence, Data and Competition SCHREPEL June 2024 OECD dis...
Artificial Intelligence, Data and Competition SCHREPEL June 2024 OECD dis...OECD Directorate for Financial and Enterprise Affairs
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