Deep Learning Digital Transformation Forecasting 
CIO Business Intelligence
JUNE 1, 2022
Cloud-connected cars are now commonplace in the mainstream connected car market that is forecast to surpass $166 billion by 2025. Meanwhile, the digital twin market is set to grow at a 50% compound annual growth rate, reaching $184.5 billion by 2030. Just starting out with analytics?
Smarten
JUNE 14, 2023
GPT, or Generative Pre-Trained Transformer, is a Large Language Model (LLM). GPT-4 has a capacity of more than 175 billion machine learning parameters, and can support many types of tasks, e.g., answering questions, providing machine translation, summarizing text, time series forecasting, etc. Contact Us to find out more.
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CIO Business Intelligence
JUNE 7, 2022
Predictive analytics applies techniques such as statistical modeling, forecasting, and machine learning to the output of descriptive and diagnostic analytics to make predictions about future outcomes. It is frequently used for economic and sales forecasting. Data analytics examples.
Jet Global
AUGUST 24, 2020
In today’s digital transformation environment, companies need their solutions to evolve with them and enable real-time insight throughout an organization. iVEDiX has delivered brilliantly curated digital solutions for some of the world’s most progressive organizations. Visit insightsoftware.com for more information.
Jedox
JULY 31, 2018
Part one of our blog series explored how people are the driving force behind the digital transformation and how it is fueled by artificial intelligence and machine learning. Modern-day forecasting, for example, relies heavily on predictive analysis. Types of Artificial Intelligence: Machine Learning, Deep Learning.
IBM Big Data Hub
MAY 17, 2024
They can provide valuable insights and forecasts to inform organizational decision-making in omnichannel commerce, enabling businesses to make more informed and data-driven decisions. And these technologies provide brands with intelligent tools, enabling more productivity and efficiency than was possible even five years ago.
Cloudera
SEPTEMBER 11, 2020
What they have learned is that often their legacy Machine Learning models (e.g. demand forecasting) based solely on historical transaction data – really missed the mark. Much of the changes we’re seeing from retail and consumer goods leaders in terms of impact are centered around the use of data and analytics.
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