What is Data Science? A Beginner’s Guide
Check out this data science concept sampler, and learn about the trade, its tricks, and how to approach it.
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Why Normalization Matters in Data Science
Explore the importance of normalization in data science, how it contrasts with standardization, and its critical role in machine learning models. This article includes Python examples for practical understanding.
Is Feature Engineering a Dying Art?
Manual feature engineering remains an integral skill. A hybrid approach combining automation with human fine-tuning offers the ideal path forward.
Data Preparation with Python: Dealing with Outliers
Learn about detecting and dealing with outliers using Python. Learn more with our latest free ebook on data cleaning and preparation.
Data Cleaning and Preprocessing for Data Science Beginners [eBook]
Explore data cleaning & preprocessing with this free ebook from Data Science Horizons. Learn workflow, use Python libraries, and apply techniques via a case study.
10 Underrated Soft Skills for Data Scientists
This article explores 10 underrated soft skills that are crucial for data scientists to thrive in their careers. These skills range from communication and empathy to adaptability and time management, with examples and evidence to support their importance in the data science field.
Understanding Bias in Data Science
Bias in data science is like a silent operator. It exists subtly in many forms, from data collection to interpretation, and if not checked, it can derail the objectivity and reliability of your analyses.
Statistical Paradoxes for Data Scientists
Here, we delve into five statistical paradoxes that every data scientist should be aware of, complete with specific examples and in-depth explanations of their significance.
Ensuring Reproducibility in Data Science
Despite the importance of reproducibility, there are several challenges in achieving it.
Thinking Clearly: A Data Scientist’s Guide to Understanding Cognitive Biases [eBook]
In Thinking Clearly: A Data Scientist’s Guide to Understanding Cognitive Biases, each chapter provides an in-depth exploration of one of a wide ranging number of cognitive biases, including its definition, examples, and the consequences it can have on decision-making and problem-solving.