Smart Data Collective

JUNE 4, 2021

Here are the chronological steps for the data science journey. First of all, it is important to understand what data science is and is not. Data science should not be used synonymously with data mining. Mathematics, statistics, and programming are pillars of data science. Use cases of data science.

Data Science 133

Data Science Exploratory Data Analysis Machine Learning Machine Learning 133

Pickl AI

JULY 30, 2024

Microsoft Azure Microsoft Azure is a cloud computing platform that provides a range of services, including storage, computing, and analytics. Some of the key tools used for Machine Learning include: Building Machine Learning Models Machine learning models make predictions or classifications based on biological data.

Cloud Computing 52

Cloud Computing Machine Learning Machine Learning Power BI 52

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.

Cloud Data 147

Cloud Data Data Science Business Intelligence Business Intelligence 147

ODSC - Open Data Science

MAY 1, 2023

Pedro Domingos, PhD Professor Emeritus, University Of Washington | Co-founder of the International Machine Learning Society Pedro Domingos is a winner of the SIGKDD Innovation Award and the IJCAI John McCarthy Award, two of the highest honors in data science and AI.

Data Science 52

Data Science Machine Learning Machine Learning Azure 52

ODSC - Open Data Science

APRIL 3, 2023

While a data analyst isn’t expected to know more nuanced skills like deep learning or NLP, a data analyst should know basic data science, machine learning algorithms, automation, and data mining as additional techniques to help further analytics. Cloud Services: Google Cloud Platform, AWS, Azure.

Analytics 52

Analytics Analytics Data Analyst Data Science 52

ODSC - Open Data Science

MAY 25, 2023

Mario Inchiosa, PhD Principal Data Scientist Manager | Microsoft Dr. Inchiosa’s current work focuses on AI-led co-innovation engagements. His past roles have included work in analytics, big data, R, SQL, data mining, and more.

Data Science 52

Data Science Machine Learning Machine Learning Database 52

Pickl AI

JANUARY 23, 2023

It is one of the most commonly used frameworks for data mining and analysis in the current scenario. Azure ML Studio Azure ML Studio is a machine learning framework that helps developers to build different machine learning models as well as the APIs. It is very easy to implement and well documented.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

DagsHub

APRIL 21, 2024

Scikit-learn Scikit-learn is a machine learning library in Python that is majorly used for data mining and data analysis. Similar to SageMaker, Azure ML offers a range of tools and services for the entire machine learning lifecycle, from data preparation and model development to deployment and monitoring.

Machine Learning 59

Machine Learning Machine Learning ML ML 59

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.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Python Natural Language Processing 52

The MLOps Blog

FEBRUARY 27, 2025

Think about it this way: it is easy to integrate GDPR-compliant services like ChatGPTs enterprise version or to use AI models in a law-compliant way through platforms such as Azures OpenAI offering , as providers take the necessary steps to ensure their platforms are compliant with regulations.

AI 64

AI AI Machine Learning Machine Learning 64

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. Summary – What value can you expect?

Data Science 246

Data Science Azure Power BI Business Intelligence 246