Smart Data Collective

JUNE 19, 2022

Companies are using AI to better understand their customers, recognize ways to manage finances more efficiently and tackle other issues. Since AI has proven to be so valuable, an estimated 37% of companies report using it. AI is particularly helpful with managing risks. How AI Can Help Suppliers Manage Risks Better.

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ODSC - Open Data Science

MARCH 11, 2024

Introducing the Topic Tracks for ODSC East 2024 — Highlighting Gen AI, LLMs, and Responsible AI ODSC East 2024 , coming up this April 23rd to 25th, is fast approaching and this year we will have even more tracks comprising hands-on training sessions, expert-led workshops, and talks from data science innovators and practitioners.

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Smart Data Collective

MAY 21, 2021

Data analytics technology can help you create the right documentation framework. You can use data mining tools to inspect archives of open-source Agile documentation from other developers. Use AI Technology to assess the performance of virtual team members. Find new open-source code to streamline development.

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ODSC - Open Data Science

AUGUST 21, 2023

Introducing the Topic Tracks for ODSC West 2023 — Highlighting Gen AI and LLMs As we progress towards the end of the year, we’re turning our full attention to ODSC West coming to the heart of the AI boom (in-person) or your computer (virtual) from October 30th — November 2nd.

Data Science 52

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IBM Journey to AI blog

SEPTEMBER 19, 2023

Overview: Data science vs data analytics Think of data science as the overarching umbrella that covers a wide range of tasks performed to find patterns in large datasets, structure data for use, train machine learning models and develop artificial intelligence (AI) applications.

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Dataconomy

JUNE 13, 2023

At its core, decision intelligence involves collecting and integrating relevant data from various sources, such as databases, text documents, and APIs. This data is then analyzed using statistical methods, machine learning algorithms, and data mining techniques to uncover meaningful patterns and relationships.

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Pickl AI

JUNE 25, 2023

Before delving deeper into the functionalities of business analytics, it is important to understand what business analytics is. The latter is the practice of using statistical techniques, data mining, predictive modelling, and Machine Learning algorithms to analyze past and present data.

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Smart Data Collective

MARCH 5, 2022

Here are some reasons that data scientists will have a strong edge over their competitors after starting a dropshipping business: Data scientists understand how to use predictive analytics technology to forecast trends. Data scientists know how to leverage AI technology to automate certain tasks.

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Towards AI

JUNE 27, 2023

In the rapidly expanding field of artificial intelligence (AI), machine learning tools play an instrumental role. Already a multi-billion-dollar industry, AI is having a profound impact on every aspect of life, business, and society. These tools are becoming increasingly sophisticated, enabling the development of advanced applications.

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Pickl AI

APRIL 15, 2024

Key Concepts and Techniques Machine Learning : This is like teaching computers to learn from data without being explicitly programmed. Data Mining : Think of data mining as digging for gold in a mountain of data. Predictive Analytics : Predictive analytics uses historical data to forecast future outcomes.

Data Science 52

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Smart Data Collective

JANUARY 19, 2022

A growing number of companies are using data analytics to better understand the mindset of their customers, provide better customer service , forecast industry trends and identify the ROI of various marketing strategies. They are also using AI tools like Canva and Hootsuite to automate many of their marketing tasks.

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Smart Data Collective

OCTOBER 20, 2020

Some of these were addressed in the Data Driven Summit 2018. Benefits include: Using data analytics to better identify your target audience Developing a stronger competitive advantage Forecasting trends with predictive analytics to anticipate future market demand. GTM marketing strategies are no exception.

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IBM Journey to AI blog

JULY 6, 2023

Data science solves a business problem by understanding the problem, knowing the data that’s required, and analyzing the data to help solve the real-world problem. Machine learning (ML) is a subset of artificial intelligence (AI) that focuses on learning from what the data science comes up with.

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Smart Data Collective

FEBRUARY 4, 2021

YouTube was launched in 2005, when big data was just a blip on the horizon. However, data analytics and AI have made video technology more versatile than ever. Clever video marketers know how to use AI and big data to their full advantage. Big Data is Changing the Future of Video Marketing.

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Heartbeat

OCTOBER 23, 2023

Image from "Big Data Analytics Methods" by Peter Ghavami Here are some critical contributions of data scientists and machine learning engineers in health informatics: Data Analysis and Visualization: Data scientists and machine learning engineers are skilled in analyzing large, complex healthcare datasets.

Machine Learning 52

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Smart Data Collective

NOVEMBER 29, 2019

Some of the changes include the following: Big data can be used to identify new link building opportunities through complicated Hadoop data-mining tools. Big data can make it easier to provide a more personalized user experience, which is key to ranking well in Google these days. Here are some of the reasons why.

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Smart Data Collective

DECEMBER 22, 2021

The good news is that big data is able to help with many of these issues. For example, a construction business can utilize project management software with sophisticated AI and data analytics algorithms to help lower the risk of construction projects going awry. Data analytics is especially useful for UX optimization.

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Data Science Blog

FEBRUARY 23, 2023

1, Data is the new oil, but labeled data might be closer to it Even though we have been in the 3rd AI boom and machine learning is showing concrete effectiveness at a commercial level, after the first two AI booms we are facing a problem: lack of labeled data or data themselves. Fine-tuning is quite easy.

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Data Science Blog

NOVEMBER 15, 2023

In addition to Business Intelligence (BI), Process Mining is no longer a new phenomenon, but almost all larger companies are conducting this data-driven process analysis in their organization. This aspect can be applied well to Process Mining, hand in hand with BI and AI. Click to enlarge!

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IBM Journey to AI blog

JULY 24, 2023

This has led to an increase in the importance of IT operations analytics (ITOA), the data-driven process by which organizations collect, store and analyze data produced by their IT services. ITOA turns operational data into real-time insights.

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Dataversity

APRIL 6, 2021

With the huge amount of online data available today, it comes as no surprise that “big data” is still a buzzword. But big data is more […]. The post The Role of Big Data in Business Development appeared first on DATAVERSITY. Click to learn more about author Mehul Rajput.

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Pickl AI

JANUARY 23, 2023

It is developed by Facebook’s AI Research Lab (FAIR) and authored by Adam Paszke, Sam Gross, Soumith Chintala, and Gregory Chanan. It is one of the most commonly used frameworks for data mining and analysis in the current scenario. It is developed with the help of languages like Python, C++, and CUDA. It’s a bit complex.

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Data Science Blog

FEBRUARY 4, 2023

In the era of Industry 4.0 , linking data from MES (Manufacturing Execution System) with that from ERP, CRM and PLM systems plays an important role in creating integrated monitoring and control of business processes.

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Smart Data Collective

OCTOBER 25, 2023

Well, it is – to the ones that are 100% familiar with it – and it involves the use of various data sources, including internal data from company databases, as well as external data, to generate insights, identify trends, and support strategic planning. In the 1990s, OLAP tools allowed multidimensional data analysis.

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Data Science Blog

JULY 23, 2023

Companies use Business Intelligence (BI), Data Science , and Process Mining to leverage data for better decision-making, improve operational efficiency, and gain a competitive edge. Process Mining offers process transparency, compliance insights, and process optimization.

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