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AutoML in Practice

The compelling Oct. 15, 2019 presentation below is on behalf of one of my favorite Meetup groups: LA Machine Learning. The talk, “AutoML in Practice,” is by Danny D. Leybzon, a Solutions Architect at Qubole, a cloud-native big data platform. Automated Machine Learning (AutoML) is one of the hottest topics in data science today, but what does it mean? This presentation gives a broad overview of AutoML, ranging from simple hyperparameter optimization all the way to full pipeline automation.

When DNNs become more human: DNNs vs Transfer Learning vs. Continual Learning

In this contributed article, Dr. Massimilliano Versace, CEO and Co-Founder of Neurala, discusses how as new approaches to deep neural networks (DNNs) and deep learning continue to emerge, it’s important to understand the differences between them. Not all DNNs are created equal, and small tweaks in their architecture sometimes have profound implications in their applicability to real-world scenarios.

Competition Uses AI to Combat Inequities in Early Childhood Education

Booz Allen Hamilton, Kaggle and PBS KIDS launched the fifth annual Data Science Bowl. This 90-day competition challenges thousands of data scientists and researchers from around the world to apply the power of artificial intelligence to combat inequities in early childhood education (ECE). More specifically, participants will create AI algorithms using anonymous gameplay data from the PBS KIDS Measure Up! App, which helps young children build math skills, to better understand children’s unique learning styles.

Topcoder On-Demand Digital Talent Platform Includes New Data Science, AI Features to Advance Enterprise Analytics

Topcoder, a Wipro company, and a technology network and on-demand digital talent platform, announced the addition of new data science and AI features to the Topcoder Platform. Highlights include native GPU support and the ability to develop advanced analytic solutions with any tool, library or cloud application service.

Micron Introduces Comprehensive AI Development Platform

Micron Technology, Inc. (Nasdaq: MU), announced a powerful new set of high-performance hardware and software tools for deep learning applications with the acquisition of FWDNXT, a software and hardware startup. When combined with advanced Micron memory, FWDNXT’s (pronounced “forward next”) artificial intelligence (AI) hardware and software technology enables Micron to explore deep learning solutions required for data analytics, particularly in IoT and edge computing.

Diveplane Introduces ALLUVION™ to Help Commercial Real Estate Investors Overcome Forecasting Challenges

Diveplane , the company keeping the humanity in artificial intelligence (AI), introduces ALLUVION ™ , its newest AI tool created specifically for the commercial real estate industry.

Kubernetes Driving Google Cloud

Kubernetes is increasingly being used with big data deployments. This trend is driving more big data apps to move to GCP, which offers homegrown support for Kubernetes. To make these workloads simpler and cheaper, there’s a need for a new solution for managing data workloads on Google Cloud Dataproc. With GCP’s CAGR estimated to grow by 64% CAGR through 2021, the cloud is now clearly a three-horse race.

Four Big Factors Shaping the Future of Data Science

In this special guest feature, Ryohei Fujimaki, Ph.D., Founder and CEO of dotData, discusses how AI and ML are having a profound impact on enterprise digital transformation becoming crucial as a competitive advantage and even for survival. As the field grows, four trends emerge, shaping data science in the next five years.

5 Ways Big Data Is Impacting Employee Benefits Packages

Big data has transformed how businesses in various industries process and analyze information in ways that were impossible before. The technology can crunch numbers and detect trends much faster than humans could without help. In this contributed article, tech blogger Caleb Danziger provides five ways big data has changed employee benefits packages and the human resources (HR) professionals responsible for keeping workers informed.

2020 Trends in Big Data: The Integration Agenda

In this contributed article, editorial consultant Jelani Harper discusses how organizations can now get the diversity of data required for meaningful machine learning results. The overhead of operating in hybrid, multi-cloud environments is less costly. The very worth of big data has increased with novel opportunities to comprehensively analyze business problems from an array of sources not previously available. However, these benefits are only realized if organizations can successfully deal with the greatest consequence of the dispersal of data to heterogeneous settings: the undue emphasis it places on data integrations.