Sign up for our newsletter and get the latest big data news and analysis.

Video Highlights: MLDataR – a Data Package for Supervised Machine Learning in R

The video presentation below is courtesy of Gary Hutson, regarding a new R package he launched recently on CRAN to provide example ML data sets for supervised machine learning problems. The data sets have examples in healthcare, but he plans to widen to include other types of data.

The insideBIGDATA IMPACT 50 List for Q1 2022

The team here at insideBIGDATA is deeply entrenched in following the big data ecosystem of companies from around the globe. We’re in close contact with most of the firms making waves in the technology areas of big data, data science, machine learning, AI and deep learning. Our in-box is filled each day with new announcements, […]

Video Highlights: Expert.ai – Executive Interview

In this interview, expert.ai’s CEO Walt Mayo gives an update on the company’s recent FY20 results. He discusses the technology that is being developed as part of the company’s Path to Lead five-year strategy and outlines how the company expects to commercialise it. He discusses the wider natural language understanding/processing (NLU/NLP) market, highlighting recent M&A activity. Finally, he outlines the key milestones the company is targeting over the next 12 months.

68% of CTOs have Implemented Machine Learning at their Organization

Research from STX Next, Europe’s largest software development company specializing in the Python programming language, has found that 68% of chief technical officers (CTOs) have implemented machine learning at their company. This makes it overwhelmingly the most popular subset of AI, with others such as natural language processing (NLP), pattern recognition and deep learning also showing considerable growth.

Best of arXiv.org for AI, Machine Learning, and Deep Learning – December 2021

In this recurring monthly feature, we will filter all the recent research papers appearing in the arXiv.org preprint server for subjects relating to AI, machine learning and deep learning – from disciplines including statistics, mathematics and computer science – and provide you with a useful “best of” list for the month.

Video Highlights: Time Series Analysis with Pandas

The topic “Time Series Analysis with Pandas” was presented by Joshua Malina, former Data Scientist at American Express, held at the 2019 Data Science Salon event in Miami. In his talk, Joshua explains how American Express utilizes Pandas for the analysis and manipulation of big amounts of time series data in an easy, flexible and powerful way.

Video Highlights: ML System Design for Continuous Experimentation

While ML model development is a challenging process, the management of these models becomes even more complex once they’re in production. Shifting data distributions, upstream pipeline failures, and model predictions impacting the very data set they’re trained on can create thorny feedback loops between development and production.

Best of arXiv.org for AI, Machine Learning, and Deep Learning – November 2021

In this recurring monthly feature, we will filter all the recent research papers appearing in the arXiv.org preprint server for subjects relating to AI, machine learning and deep learning – from disciplines including statistics, mathematics and computer science – and provide you with a useful “best of” list for the month.

Video Highlights: Andrew Ng on Career Advice / Reading Research Papers

Stanford University, CS230 is a widely revered course to learn the foundations of Deep Learning, understand how to build neural networks, and learn how to lead successful machine learning projects. Students learn about Convolutional networks, RNNs, LSTM, Adam, Dropout, BatchNorm, Xavier/He initialization, and more. In the video lecture below, Andrew Ng Adjunct Professor, Computer Science, presents Lecture 8 which touches on career advice and also tips for reading research papers.

World Data League Launches Public Report with the Competition’s Best Solutions and Strategies

The work of more than 100 data scientists, over 14 challenges in line with the 11th United Nations Goal – Sustainable Cities and Communities – is now available for consultation and use through an open report released by the World Data League.