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Articles by: Faithe Day

Faithe Day

Faithe J. Day is a writer, researcher, and educator with a BA in English and Digital Humanities and a PhD in Communication Studies. Over the past few years, she has been awarded research fellowships focused on data science, curation, and education, during which she developed projects that critique the role of information and technology within society and culture. Through a focus on the ethics of data collection and sharing, her writing explores the politics of platforms, the role of social media in society, and the future of algorithms and artificial intelligence.

Top Data Visualization Tools and Software

Uncover the significant role of data visualization tools and software in the field of data science, from simplifying the analysis process to communicating key insights in a visually compelling manner. Explore the top five tools including Tableau and Google Charts, and their applications in various industries, from business intelligence to product development.

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Data Visualization vs. Data Storytelling

Data visualization and data storytelling are both crucial skills for data science professionals, allowing them to effectively communicate insights and findings to a diverse audience. Even though visualization tools like graphs and charts are common, it is storytelling that provides context and comprehension, helping viewers understand the significance of the data presented.

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Top Tools to Build Machine Learning Models

Uncover the intricacies of machine learning models, their categorizations, and how they facilitate pattern recognition, data organization, and automation in data science processes. Also, explore the top five tools for building these models, including Microsoft Azure Machine Learning, Google TensorFlow, RapidMiner, Apache Mahout, and scikit-learn, and understand their key features and specialties.

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Top 10 Algorithms for Data Science

Explore the world of data science algorithms and artificial intelligence that professionals use to automate tasks and complete data science projects. From linear regression to artificial neural networks, discover the essential algorithms that form the foundation of machine learning models and automated systems.

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How to Use Automation and Machine Learning in Data Science

Shape your future with the expanding opportunities in the Science, Technology, Engineering, and Mathematics (STEM) fields, specifically in the data science industry. Whether you're a student or professional, you can take advantage of the cross-section between software engineering and data science, leveraging both sets of skills to create innovative solutions and products.

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Why Software Engineers Should Learn Data Science

STEM fields, particularly in data science, offer extensive employment opportunities, with many professionals interested in transitioning their skills into data science roles. Discover the similarities, differences, and transferable skills between software engineering and data science, and explore how expanding your knowledge in data science can benefit your career in software engineering.

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Why Every Data Scientist Should Know Beautiful Soup

Delve into the fascinating world of data science and learn how the Python library, Beautiful Soup can enhance your projects—particularly in the intersection of data science and development. This article delves into how Beautiful Soup can be used to parse web pages, perform web scraping, create images and databases, and facilitate machine learning and automation processes, enhancing your skills and expanding your opportunities within the industry.

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Why Every Data Scientist Should Know NumPy

Delve into the world of data science with Python's renowned open-source library, NumPy, celebrated for its advanced functionalities in creating arrays and executing mathematical operations. Whether you're a Data Scientist, a coder, or an academic researcher, discover the expansive nature of NumPy's applications, from numerical computing to machine learning, and elevate your programming prowess.

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