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Introduction to applied data science 101: Key concepts and methodologies 

Data Science Dojo

It directly focuses on implementing scientific methods and algorithms to solve real-world business problems and is a key player in transforming raw data into significant and actionable business insights. Machine learning algorithms Machine learning forms the core of Applied Data Science.

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

IBM Journey to AI blog

Machine learning works on a known problem with tools and techniques, creating algorithms that let a machine learn from data through experience and with minimal human intervention. It processes enormous amounts of data a human wouldn’t be able to work through in a lifetime and evolves as more data is processed.

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Best Resources for Kids to learn Data Science with Python

Pickl AI

Accordingly, there are many Python libraries which are open-source including Data Manipulation, Data Visualisation, Machine Learning, Natural Language Processing , Statistics and Mathematics. To obtain practical expertise, run the algorithms on datasets. It can be easily ported to multiple platforms.

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8 Best Programming Language for Data Science

Pickl AI

Additionally, its natural language processing capabilities and Machine Learning frameworks like TensorFlow and scikit-learn make Python an all-in-one language for Data Science. Its speed and performance make it a favored language for big data analytics, where efficiency and scalability are paramount. About Pickl.AI

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Introduction to R Programming For Data Science

Pickl AI

Packages like caret, random Forest, glmnet, and xgboost offer implementations of various machine learning algorithms, including classification, regression, clustering, and dimensionality reduction. Packages like dplyr, data.table, and sparklyr enable efficient data processing on big data platforms such as Apache Hadoop and Apache Spark.