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How to become a data scientist – Key concepts to master data science

Data Science Dojo

Algorithms: Decision trees, random forests, logistic regression, and more are like different techniques a detective might use to solve a case. Overfitting and Underfitting: These are common problems in machine learning, like getting too caught up in small details or missing the big picture.

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How to become a data scientist – Key concepts to master data science

Data Science Dojo

Algorithms: Decision trees, random forests, logistic regression, and more are like different techniques a detective might use to solve a case. Overfitting and Underfitting: These are common problems in machine learning, like getting too caught up in small details or missing the big picture.

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Big Data Syllabus: A Comprehensive Overview

Pickl AI

Summary: A comprehensive Big Data syllabus encompasses foundational concepts, essential technologies, data collection and storage methods, processing and analysis techniques, and visualisation strategies. Fundamentals of Big Data Understanding the fundamentals of Big Data is crucial for anyone entering this field.

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How to become a data scientist

Dataconomy

Machine learning Machine learning is a key part of data science. It involves developing algorithms that can learn from and make predictions or decisions based on data. Familiarity with regression techniques, decision trees, clustering, neural networks, and other data-driven problem-solving methods is vital.

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What is Data-driven vs AI-driven Practices?

Pickl AI

4 Steps to Combine Both Approaches Data-driven and AI-driven modelling involves integration in well-defined, structured steps where each surely can assure a mix of efficiency and insight with a broader view. Unify Data Sources Collect data from multiple systems into one cohesive dataset.

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

IBM Journey to AI blog

While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. What is data science? This post will dive deeper into the nuances of each field.

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Must-Have Skills for a Machine Learning Engineer

Pickl AI

Decision Trees These trees split data into branches based on feature values, providing clear decision rules. Knowledge of Cloud Computing and Big Data Tools As complex Machine Learning (ML) models grow, robust infrastructure for large datasets and intensive computations becomes increasingly important.