Data Science 101

OCTOBER 31, 2019

This data alone does not make any sense unless it’s identified to be related in some pattern. Data mining is the process of discovering these patterns among the data and is therefore also known as Knowledge Discovery from Data (KDD). Machine learning provides the technical basis for data mining.

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Pickl AI

OCTOBER 29, 2024

Summary: This article delves into five real-world data science case studies that highlight how organisations leverage Data Analytics and Machine Learning to address complex challenges. This blog explores five compelling case studies that illustrate the practical applications of Data Science in real-world scenarios.

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Towards AI

JUNE 27, 2023

Last Updated on June 27, 2023 by Editorial Team Source: Unsplash This piece dives into the top machine learning developer tools being used by developers — start building! In the rapidly expanding field of artificial intelligence (AI), machine learning tools play an instrumental role.

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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.

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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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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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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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Mlearning.ai

APRIL 8, 2023

One tool that can help marketers gain valuable insights into the behavior and preferences of their customers is predictive analytics, which is powered by artificial intelligence (AI). We’ll look at how predictive analytics works and what it can do for businesses in this piece. How does Predictive Analytics Work?

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IBM Journey to AI blog

JULY 6, 2023

While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. What is data science? What is machine learning?

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Dataconomy

MAY 17, 2024

Given your extensive background in administration and management, how do you envision specific data science tools, such as predictive analytics, machine learning, and data visualization, and methodologies like data mining and big data analysis, could enhance public administration and investment management?

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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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Smart Data Collective

NOVEMBER 12, 2021

Big data technology has been instrumental in changing the direction of countless industries. Companies have found that data analytics and machine learning can help them in numerous ways. We talked about the benefits of outsourcing IoT and other data science obligations. Global companies spent over $92.5

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Pickl AI

JANUARY 23, 2023

Introduction to Machine Learning Frameworks In the present world, almost every organization is making use of machine learning and artificial intelligence in order to stay ahead of the competition. So, let us see the most popular and best machine learning frameworks and their uses.

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Smart Data Collective

JUNE 19, 2022

You can use predictive analytics tools to anticipate different events that could occur. You can leverage machine learning to drive automation and data mining tools to continue researching members of your supply chain and statements your own customers are making. Cloud-based applications can also help.

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Dataconomy

MAY 10, 2023

Open-source business intelligence (OSBI) is commonly defined as useful business data that is not traded using traditional software licensing agreements. This is one alternative for businesses that want to aggregate more data from data-mining processes without buying fee-based products.

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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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Analytics Vidhya

JUNE 28, 2023

No matter how excellent your services or products are or how unique they are, it is unimportant if you can’t market them effectively. Worldwide, small- and large-scale business owners are attempting to stay up with the quick-changing marketing developments.

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Data Science Blog

NOVEMBER 15, 2023

As Task Mining provides a clearer insight into specific sub-processes, program managers and HR managers can also understand which parts of the process can be automated through tools such as RPA. So whenever you hear that Process Mining can prepare RPA definitions you can expect that Task Mining is the real deal.

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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

MAY 29, 2024

Summary: Data Science is becoming a popular career choice. 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.

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Smart Data Collective

FEBRUARY 4, 2021

You can use big data to help identify your objectives. You can research goals that other marketers have used with data mining tools and build your own strategies around them. In order to do this, you need to use predictive analytics tools to better assess the behavior of your users. Control Your Narrative.

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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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Pickl AI

AUGUST 27, 2024

Summary: Python simplicity, extensive libraries like Pandas and Scikit-learn, and strong community support make it a powerhouse in Data Analysis. It excels in data cleaning, visualisation, statistical analysis, and Machine Learning, making it a must-know tool for Data Analysts and scientists.

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phData

JUNE 28, 2023

By integrating KNIME with Snowflake, you can automate data integration, transformation, analysis, and reporting tasks, reducing manual effort and increasing productivity. While Snowflake provides the ability to store and query data at scale, KNIME empowers you to extract valuable insights from that data.

Machine Learning 52

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ODSC - Open Data Science

AUGUST 21, 2023

Machine Learning and Deep Learning This track gathers together the creators and top practitioners in the rapidly expanding fields of deep learning and machine learning to discuss the latest advances, trends, and models in these fields.

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Pickl AI

SEPTEMBER 23, 2024

Data Analysis Data Analysis involves cleaning, processing, and analysing data to uncover patterns, trends, and relationships. Machine Learning Machine Learning (ML) is a crucial component of Data Science. It enables computers to learn from data without explicit programming.

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IBM Journey to AI blog

JULY 24, 2023

ITOA turns operational data into real-time insights. It is often a part of AIOps , which uses artificial intelligence (AI) and machine learning to improve the overall DevOps of an organization so the organization can provide better service. It aims to understand what’s happening within a system by studying external data.

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Pickl AI

OCTOBER 15, 2024

Diagnostic Analytics Diagnostic analytics goes a step further by explaining why certain events occurred. It uses data mining , correlations, and statistical analyses to investigate the causes behind past outcomes. It analyses patterns to predict trends, customer behaviours, and potential outcomes.

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Smart Data Collective

MARCH 30, 2022

Companies that know how to leverage analytics will have the following advantages: They will be able to use predictive analytics tools to anticipate future demand of products and services. They can use data on online user engagement to optimize their business models. These algorithms are getting better all the time.

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ODSC - Open Data Science

MARCH 11, 2024

Deploying Trustworthy Generative AI Stable Diffusion: Advancing the Text-to-Image Paradigm Multimodal Retrieval Augmented Generation Machine Learning This track gathers together the creators and top practitioners in the rapidly expanding fields of deep learning and machine learning to discuss the latest advances, trends, and models in these fields.

Data Science 52

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Pickl AI

APRIL 15, 2024

Summary: Data Science courses with placement guarantee job security through practical training and mentorship. Accreditation, faculty expertise, and industry partnerships validate credibility, while a comprehensive curriculum covers essential topics like Python and machine learning.

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Heartbeat

OCTOBER 23, 2023

Revolutionizing Healthcare through Data Science and Machine Learning Image by Cai Fang on Unsplash Introduction In the digital transformation era, healthcare is experiencing a paradigm shift driven by integrating data science, machine learning, and information technology.

Machine Learning 52

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Pickl AI

OCTOBER 14, 2024

Role in Extracting Insights from Raw Data Raw data is often complex and unorganised, making it difficult to derive useful information. Data Analysis plays a crucial role in filtering and structuring this data. Techniques Regression: Predicting future outcomes based on relationships in past data.

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Pickl AI

JANUARY 15, 2025

Data Mining Tools Data mining tools analyse large datasets to discover hidden patterns or relationships within the data. They employ techniques from statistics, Machine Learning, and database systems to reveal insights that can inform strategic decisions.

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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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Pickl AI

JULY 12, 2024

Summary: This guide explores Artificial Intelligence Using Python, from essential libraries like NumPy and Pandas to advanced techniques in machine learning and deep learning. Introduction Artificial Intelligence (AI) transforms industries by enabling machines to mimic human intelligence.

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Pickl AI

SEPTEMBER 11, 2024

Industries like healthcare, automotive, and electronics are increasingly adopting AI, Machine Learning, IoT, and robotics. As businesses transform, the need for experts with a master’s degree in Data Science becomes crucial. This can lead to roles such as senior Data Scientist, Data Science manager, or even chief data officer.

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