Pickl AI

OCTOBER 29, 2024

GE optimised supply chain management, achieving a 15% cost reduction through predictive analytics. 5 Data Science Case Studies From healthcare to finance, these examples showcase the versatility and impact of Data Science across diverse sectors. Frequently Asked Questions What is Data Science?

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IBM Journey to AI blog

SEPTEMBER 19, 2023

Though you may encounter the terms “data science” and “data analytics” being used interchangeably in conversations or online, they refer to two distinctly different concepts. For example, retailers can predict which stores are most likely to sell out of a particular kind of product.

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IBM Journey to AI blog

JULY 6, 2023

Because the datasets are unstructured, though, it can be complicated and time-consuming to interpret the data for decision-making. That’s where data science comes in. The term data science was first used in the 1960s when it was interchangeable with the phrase “computer science.”

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Pickl AI

MAY 29, 2024

Mastering programming, statistics, Machine Learning, and communication is vital for Data Scientists. A typical Data Science syllabus covers mathematics, programming, Machine Learning, data mining, big data technologies, and visualisation. What does a typical Data Science syllabus cover?

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Pickl AI

APRIL 15, 2024

It’s like being a detective, but instead of solving crimes, we uncover hidden patterns and trends in data to solve complex problems and make informed decisions. Almost every industry relies on Data Science, from healthcare to finance, to gain insights, improve efficiency, and innovate.

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Pickl AI

SEPTEMBER 23, 2024

Understanding Data Science Data Science is a multidisciplinary field that uses scientific methods, algorithms, and systems to extract knowledge and insights from structured and unstructured data. Data Science helps organisations make informed decisions by transforming raw data into valuable information.

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Pickl AI

JULY 12, 2024

Pandas: A powerful library for data manipulation and analysis, offering data structures and operations for manipulating numerical tables and time series data. Scikit-learn: A simple and efficient tool for data mining and data analysis, particularly for building and evaluating machine learning models.

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