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A Gentle Introduction to Principal Component Analysis (PCA) in Python

Flipboard

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Data science vs. machine learning: What’s the difference?

IBM Journey to AI blog

Other challenges include communicating results to non-technical stakeholders, ensuring data security, enabling efficient collaboration between data scientists and data engineers, and determining appropriate key performance indicator (KPI) metrics.

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Where AI is headed in the next 5 years?

Pickl AI

Machine Learning and Neural Networks (1990s-2000s): Machine Learning (ML) became a focal point, enabling systems to learn from data and improve performance without explicit programming. Techniques such as decision trees, support vector machines, and neural networks gained popularity.

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What Does the Modern Data Scientist Look Like? Insights from 30,000 Job Descriptions

ODSC - Open Data Science

Natural Language Processing (NLP) has emerged as a dominant area, with tasks like sentiment analysis, machine translation, and chatbot development leading the way. Scala is worth knowing if youre looking to branch into data engineering and working with big data more as its helpful for scaling applications.