Smart Data Collective

SEPTEMBER 16, 2020

Predictive analytics, sometimes referred to as big data analytics, relies on aspects of data mining as well as algorithms to develop predictive models. The applications of predictive analytics are extensive and often require four key components to maintain effectiveness. Data Sourcing.

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Pickl AI

FEBRUARY 21, 2023

Accordingly, data collection from numerous sources is essential before data analysis and interpretation. Data Mining is typically necessary for analysing large volumes of data by sorting the datasets appropriately. What is Data Mining and how is it related to Data Science ? What is Data Mining?

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Pickl AI

OCTOBER 3, 2024

Summary: Predictive analytics utilizes historical data, statistical algorithms, and Machine Learning techniques to forecast future outcomes. This blog explores the essential steps involved in analytics, including data collection, model building, and deployment. What is Predictive Analytics?

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ODSC - Open Data Science

NOVEMBER 19, 2024

Predictive analytics is changing the way businesses operate, helping them make smarter decisions. By using data and technology, it can predict future trends, customer behavior, and much more. This article explains how retail and finance businesses use predictive analytics to improve their operations and grow.

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Towards AI

JUNE 27, 2023

Offering features like TensorBoard for data visualization and TensorFlow Extended (TFX) for implementing production-ready ML pipelines, TensorFlow stands out as a comprehensive solution for both beginners and seasoned professionals in the realm of machine learning.

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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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