IBM Journey to AI blog

SEPTEMBER 19, 2023

Business users will also perform data analytics within business intelligence (BI) platforms for insight into current market conditions or probable decision-making outcomes. Many functions of data analytics—such as making predictions—are built on machine learning algorithms and models that are developed by data scientists.

Data Science 94

Data Science Analytics Analytics Data Scientist 94

Data Science Dojo

JULY 3, 2024

Machine Learning : Supervised and unsupervised learning algorithms, including regression, classification, clustering, and deep learning. Big Data Technologies : Handling and processing large datasets using tools like Hadoop, Spark, and cloud platforms such as AWS and Google Cloud.

Data Science 150

Data Science Machine Learning Machine Learning Data Visualization 150

ODSC - Open Data Science

OCTOBER 7, 2024

It isn’t just about writing code or creating algorithms — it requires robust pipelines that handle data, model training, deployment, and maintenance. Data Preparation: Cleaning and transforming raw data to make it usable for machine learning. Model Training: Running computations to learn from the data.

Machine Learning 52

Machine Learning Machine Learning AI AI 52

DataSeries

AUGUST 15, 2024

Data Engineering Career: Unleashing The True Potential of Data Problem-Solving Skills Data Engineers are required to possess strong analytical and problem-solving skills to navigate complex data challenges. Hadoop, Spark).

Data Engineering 40

Data Engineering Data Engineering Data Engineering Data Engineer 40

ODSC - Open Data Science

JANUARY 7, 2025

Just as a writer needs to know core skills like sentence structure and grammar, data scientists at all levels should know core data science skills like programming, computer science, algorithms, and soon. Data Engineering Data engineering remains integral to many data science roles, with workflow pipelines being a key focus.

Data Scientist 40

Data Scientist Data Science Machine Learning Machine Learning 40

Pickl AI

DECEMBER 26, 2024

Key data sources include social media platforms, web analytics tools, customer feedback systems, and IoT devices, all of which contribute to a rich tapestry of actionable insights. Role of Analytics Tools in Big Data Analytics tools like Hadoop , Tableau , and predictive platforms make Big Data manageable.

Big Data 52

Big Data Big Data Big Data Analytics Big Data Analytics 52

DagsHub

OCTOBER 23, 2024

With proper unstructured data management, you can write validation checks to detect multiple entries of the same data. Continuous learning: In a properly managed unstructured data pipeline, you can use new entries to train a production ML model, keeping the model up-to-date.

Machine Learning 52

Machine Learning Machine Learning Data Lakes AI 52

Pickl AI

OCTOBER 10, 2024

Role of Data Transformation in Analytics, Machine Learning, and BI In Data Analytics, transformation helps prepare data for various operations, including filtering, sorting, and summarisation, making the data more accessible and useful for Analysts. Why Are Data Transformation Tools Important?

Data Quality 52

Data Quality AWS Machine Learning Machine Learning 52

ODSC - Open Data Science

APRIL 26, 2023

As models become more complex and the needs of the organization evolve and demand greater predictive abilities, you’ll also find that machine learning engineers use specialized tools such as Hadoop and Apache Spark for large-scale data processing and distributed computing.

Data Analyst 52

Data Analyst Machine Learning Machine Learning Power BI 52