Machine learning platforms

Enterprises need to make smart investments in machine learning platforms. With a range of features and price tags, making the right choice can seem like a daunting task. Discover machine learning platform comparison content, information on getting started with machine learning algorithms and best practices to gain the most from projects.

December 01, 2020 01 Dec'20
AWS releases machine learning services for industrial clients

AWS released a mix of hardware, software and cloud-based services to help manufacturing clients better manage workplace safety and machine health.
September 17, 2020 17 Sep'20
Rivals Cloudian, Scality embrace all-flash object storage

Primarily used as a disk repository, object storage use cases are evolving to support workloads that need fast flash. Rivals Cloudian and Scality provide the latest evidence.
August 17, 2020 17 Aug'20
Does technology increase the problem of racism and discrimination?

According to a publication from the MIT Technology Review, technology promotes racism. Most facial recognition algorithms discriminate against the Black population. And even certain concepts or technological terminology tend to be offensive, ...
July 15, 2020 15 Jul'20
Care provider uses automated machine learning in healthcare

An assisted living and transitional care provider uses DataRobot to automate the process of building and deploying machine learning models, enabling it to deploy models quickly.

Bring yourself up to speed with our introductory content

AWS SageMaker training, making machine learning accessible

Making machine learning more accessible and helping developers with AWS SageMaker training is at the core of Julien Simon's book, 'Learn Amazon SageMaker.' Continue Reading
Introduction to using machine learning

The first part of our machine learning series, excerpted from training materials for Arcitura's Machine Learning Specialist certification, introduces algorithms, models and model training. Continue Reading
Training GANs relies on calibrating 2 unstable neural networks

Understanding the complexities and theory of dueling neural networks can carve out a path to successful GAN training. Continue Reading

Weigh the pros and cons of technologies, products and projects you are considering.

Data science vs. machine learning vs. AI: How they work together

Data science, machine learning and AI are central to analytics and other enterprise uses. Here's what each involves and how combining them benefits organizations. Continue Reading
KDD in data mining assists data prep for machine learning

While data scientists are often familiar with data mining, the deeper knowledge discovery in databases (KDD) procedure can help prepare data to train machine learning algorithms. Continue Reading
14 most in-demand data science skills you need to succeed

The demand for data scientists continues to grow, but the job requires a combination of technical and soft skills. Here are 14 key skills for effective data scientists. Continue Reading

Learn to apply best practices and optimize your operations.

Free machine learning course: Using ML algorithms, practices and patterns

This 13-lesson series offers an overview of machine learning and its applications for those hoping to break into the machine learning job market or learn more about this technology. Continue Reading
Tackling the AI bias problem at the origin: Training data

Though data bias may seem like a back-end issue, the enterprise implications of an AI software using biased data can derail model implementation. Continue Reading
The data science process: 6 key steps on analytics applications

The data science process includes a set of steps that data scientists take to gather, prepare and analyze data and present the analytics results to business users. Continue Reading

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9 data quality issues that can sideline AI projects

The quality of your data affects how well your AI and machine learning models will operate. Getting ahead of these nine data issues will poise organizations for successful AI models. Continue Reading
How to troubleshoot 8 common autoencoder limitations

Autoencoders' ability for automated feature extraction, data preparation, and denoising are complicated by their common problems and limitations in usage. Continue Reading
Data science's ongoing battle to quell bias in machine learning

Machine learning expert Ben Cox of H2O.ai discusses the problem of bias in predictive models that confronts data scientists daily and his techniques to identify and neutralize it. Continue Reading