Data Science Dojo

FEBRUARY 18, 2023

This blog outlines a collection of 12 AI tools that can assist with day-to-day activities and make tasks more efficient and streamlined.  The development of Artificial Intelligence has gone through several phases over the years. In the 1970s and 1980s, AI research shifted to knowledge-based systems and expert systems.

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Dataconomy

SEPTEMBER 4, 2023

Predictive analytics: Predictive analytics leverages historical data and statistical algorithms to make predictions about future events or trends. It’s particularly valuable for forecasting demand, identifying potential risks, and optimizing processes.

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Pickl AI

OCTOBER 25, 2023

How Big Data and AI Work Together: Synergies & Benefits: The growing landscape of technology has transformed the way we live our lives. of companies say they’re investing in Big Data and AI. In this blog, our focus will revolve around Big Data and Artificial Intelligence.

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IBM Journey to AI blog

MAY 17, 2024

Key takeaways By implementing effective solutions for AI in commerce, brands can create seamless, personalized buying experiences that increase customer loyalty, customer engagement, retention and share of wallet across B2B and B2C channels. Successful integration of AI in commerce depends on earning and keeping consumer trust.

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Smart Data Collective

JULY 19, 2019

When Alan Turing invented the first intelligent machine , few could have predicted that the advanced technology would become as widespread and ubiquitous as it is today. Since then, companies have adopted AI for pretty much everything , from self-driving cars to medical technology to banking. AI enhances user experience.

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Pickl AI

JULY 20, 2023

Root cause analysis is a typical diagnostic analytics task. 3. Predictive Analytics Projects: Predictive analytics involves using historical data to predict future events or outcomes. NLP techniques help extract insights, sentiment analysis, and topic modeling from text data.

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Heartbeat

OCTOBER 23, 2023

These professionals apply their expertise to analyze large and complex healthcare datasets, extract meaningful insights, build predictive models, and create innovative solutions that drive evidence-based decision-making and enhance patient outcomes. Another notable application is predictive analytics in healthcare.

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