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Data Science from Scratch VS The Art of Data Science

Compare Data Science from Scratch VS The Art of Data Science and see what are their differences

Data Science from Scratch logo Data Science from Scratch

Data Science and Python, starting at zero

The Art of Data Science logo The Art of Data Science

A guide for anyone who works with data
  • Data Science from Scratch Landing page
    Landing page //
    2019-07-07
  • The Art of Data Science Landing page
    Landing page //
    2022-07-12

Data Science from Scratch features and specs

  • Hands-On Learning
    The book encourages a practical approach to learning data science by implementing algorithms and concepts from scratch, helping readers understand the underlying mechanics.
  • Comprehensive Coverage
    It covers a wide range of fundamental topics in data science such as statistics, data visualization, linear algebra, and machine learning, providing a solid foundation.
  • Python-Based
    Since the book is centered around Python, a popular programming language in data science, it is accessible to a large audience already familiar with Python.
  • Developer-Friendly
    The content is ideal for developers looking to transition into data science, as it focuses on programming and algorithmic aspects of data science.

Possible disadvantages of Data Science from Scratch

  • Steep Learning Curve
    Beginners may find the approach challenging if they do not have prior programming experience in Python or understanding of mathematical concepts.
  • Lack of Real-World Applications
    The focus on building from scratch may lack the practical application perspective and real-world examples that some learners might seek.
  • Outdated Information
    As data science is a rapidly evolving field, some methodologies, tools, or libraries discussed might be outdated or less common in the industry today.
  • Less Emphasis on Tools
    The book emphasizes building concepts from scratch over familiarizing readers with powerful existing data science libraries and tools like TensorFlow or PyTorch.

The Art of Data Science features and specs

  • Practical Approach
    The book offers a hands-on, applied perspective to data science, focusing on real-world problems and solutions.
  • Clear and Concise
    The authors deliver complex concepts in a straightforward and accessible manner, making it easier for readers to grasp essential ideas.
  • Focus on Interpretation
    There is an emphasis on interpreting and communicating results, which is crucial for data-driven decision-making.
  • Interdisciplinary Nature
    It covers aspects of both statistical techniques and computational tools, providing a holistic view of data science practice.

Possible disadvantages of The Art of Data Science

  • Limited Technical Depth
    Some readers may find the technical aspects to be too introductory, lacking depth in complex algorithmic explanations.
  • Narrow Audience
    The content is geared more towards beginners and intermediate practitioners, leaving advanced data scientists wanting more.
  • Few Code Examples
    The book doesn't provide extensive code snippets or programming tutorials, which might not cater to those looking for hands-on coding guidance.
  • Lack of Cutting-Edge Techniques
    The content may not cover the latest advancements or trends in data science, potentially making it feel outdated for seasoned professionals.

Data Science from Scratch videos

Data Science from Scratch by Joel Grus: Review | Learn python, data science and machine learning

More videos:

  • Review - Data Science Full Course 2020 | Data Science For Beginners | Data Science from Scratch | Simplilearn

The Art of Data Science videos

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Category Popularity

0-100% (relative to Data Science from Scratch and The Art of Data Science)
AI
41 41%
59% 59
Data Science And Machine Learning
Note Taking
0 0%
100% 100
Reporting & Dashboard
100 100%
0% 0

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What are some alternatives?

When comparing Data Science from Scratch and The Art of Data Science, you can also consider the following products

Gyana - Intuitive easy-to-use report and dashboard tool to stop wasting time on repetitive and tedious tasks.

Deepnote - A collaboration platform for data scientists

Amie - GitHub for research and data science

Daisho - Become a data science superhero, no code, no math

DataQuest Beta - Codecademy for Data Science

Jovian - Learn Data Science and ML with free hands-on online courses